เงื่อนไขการค้นหา

ประสบการณ์:

3 ปีขึ้นไป

ทักษะ:

Software Development, Windows Server, Automation, Python, Oracle, Apache, VMware, Linux, SQL, GIS

ประเภทงาน:

งานประจำ

• Act as the single point of contact (SPOC) for back-office users, handling incoming tickets via ITSM and calls through the central App Support Hotline [Ext. 7777]..
• Monitor application health, alert dashboards, and server resources; perform initial troubleshooting, and execute standard remediation according to SOPs.
• Log and document all issues in the ITSM system with high accuracy, ensuring proper categorization and routing to support >90% triage precision.
• Escalate unresolved or critical incidents (P1/P2) immediately to the Software Development Team Leader, SRE, or Server teams using the defined escalation protocols.
• Assist in testing application updates, system patches, and rollback procedures under the change management guidelines.
• Create and maintain technical runbooks, troubleshooting guides, and knowledge base articles, utilizing AI.
• Bachelor's degree in Computer Science, Computer Engineering, Information Technology, or a related field.
• 1-3 years of experience in Application Support, IT Helpdesk, Technical Support, or Operations roles. (Highly motivated fresh graduates are also welcome to apply).
• Familiarity with ITSM ticketing tools (preferably ManageEngine or Jira Service Desk).
• Ability to work under pressure, manage multi-tasking demands, and resolve user issues with a strong customer-service mindset.
• Strong problem-solving, analytical, and logical-thinking skills.
• Good team contributor who communicates technical issues clearly and collaborates effectively with cross-functional teams.
• Specific knowledge and skill / ความรู้เฉพาะตำแหน่ง.
• Basic Database & Queries: Ability to write and run basic SQL queries (MS-SQL, Postgre, or Oracle) for investigation and data extraction.
• Infrastructure Basics: Basic knowledge of Windows Server, Active Directory, Linux CentOS/RedHat, and virtualization (VMware).
• System Monitoring & Transfer: Familiarity with file transfer protocols (SFTP/FTP), GoAnywhere, Apache Airflow and system monitoring tools (metrics, logs, alerts).
• Financial Business Flow: Basic understanding of securities trading lifecycle, mutual funds, or back-office batch processing.
• Automation Basics: Basic scripting skills (Python, PowerShell, or Bash) is a strong advantage.
• Apply now ".

ทักษะ:

Git, Apache

ประเภทงาน:

งานประจำ

• Architectural Artifacts: Serves as the primary author of the High-Level Design (HLD) and the Architecture Definition Document (ADD) using arc42 standards.
• System Modeling: Utilizes the C4 Model to create detailed component models and documentation that eliminate developer interpretation..
• Technical Governance: Ensures project-level "Gate" success and prevents localized technical debt or security leaks..
• Design Precision: Defines System Building Blocks (SBBs) and formal API Specifications(Open API/Swagger)..
• Decision Management: Records all architectural trade-offs as Architecture Decision Records (ADRs) in a version-controlled repository..
• Cloud & Container Technology.
• Platform Expertise: Architectural design and management within OpenShift (OCP) and Kubernetes (K8s) environments.
• Secret & Key Management: Integration of Vault and Hardware Security Modules (HSM)for robust cryptographic operations and secret management.
• Service Mesh: Implementation of Istio for traffic management and secure communication.
• Governance: Applying Git Ops Governance and integrating security scanning into CI/CD pipelines.
• Banking Security & Regulatory Standards.
• Cyber Resilience: Alignment with the Bank of Thailand (BoT) Cyber Resilience Framework to ensure systemic safety..
• Data Privacy (PDPA): Designing field-level encryption and masking for Personally Identifiable Information (PII) to comply with PDPA regulations..
• Identity & Access: Enforcing Multi-Factor Authentication (MFA) and utilizing OIDC/OAuth2 and JWT (JWS/JWE) for secure identity..
• Audit Readiness: Acting as a technical contact for BoT IT Examinations and ensuring all design assets are ready for regulatory audit..
• Payment Standards: Knowledge of PCI-DSS for cardholder data security.
• Technical Skills & Patterns.
• Microservices Patterns: Expertise in Database-per-service, Circuit Breaker, Sidecar, and Saga Patterns (Distributed Transactions).
• Messaging & Integration: Proficiency in Apache Kafka (ensuring Idempotency), gRPC, and REST (Level 3)..
• Distributed Systems: Application of CAP Theorem and Event Sourcing in high-availability environments..
• Resilience: Implementing Strangler Fig patterns for legacy migration and automated Disaster Recovery (DRP) plans..
• Bachelor s Degree in Computer Science or equivalent work experience.
• 10 year or more years of relevant work experience.
• Experience defining, applying and enforcing architecture standards, guidelines and policies to the organization.
• Good communication skills, abilities to discuss with technical and non-technical people, present ideas and motivate people.
• Background knowledge on banking.
• Messaging or streaming middleware such as RabbitMQ or Kafka.
• Experience with distributed architectures, SOA, microservices and Platform-as-a-Service (PaaS).
• Experience with Agile.
• Experience with high availability, high-scale, and performance systems.
• Why You ll Love Working With Us.
• At Krungsri Nimble, you ll join a passionate team working at the intersection of technology and banking innovation. We embrace an agile mindset where you ll have real ownership and the opportunity to influence system design and business outcomes. In our collaborative and transparent environment, we prioritize continuous learning to stay ahead of the curve. If you're looking for a role where you can make a responsible impact, grow your expertise, and help shape the future of digital banking, this is where you belong.
• Apply now and build something transformative with us.

ประสบการณ์:

3 ปีขึ้นไป

ทักษะ:

Architecture, Automation, Big Data, Power BI, Python, Oracle, Hadoop, Apache, SQL, ETL

ประเภทงาน:

งานประจำ

• Design, develop, and maintain robust data pipelines using Apache Airflow, SSIS, PySpark, and Talend to ingest, transform, and load large-scale datasets (300M+ rows) from multiple sources.
• Manage and optimize relational databases including Oracle and SQL Server, ensuring high performance and scalability for analytical workloads.
• Design, build, and maintain cloud data platforms and warehousing solutions using AWS services such as Redshift and S3, alongside ClickHouse for high-performance analyti ...
• Develop and maintain OLAP solutions using SSAS for advanced reporting and analytics, including cube design, partitioning, and aggregation strategies.
• Implement ETL processes for structured and semi-structured data using tools such as Talend and PySpark, ensuring data quality, consistency, and compliance with industry standards.
• Collaborate with BI team, Actuarial Team and business stakeholders to understand requirements and deliver efficient data models and solutions.
• Monitor and improve data pipeline performance, troubleshoot bottlenecks, and implement best practices for parallel processing and resource optimization.
• Ensure data security and compliance with insurance industry regulations and company policies.
• Leverage big data technologies such as Apache Spark for distributed processing and advanced data transformations.
• Automate workflows and scheduling using Airflow DAGs, ensuring reliability and scalability of data operations.
• Document data architecture, processes, and standards, and provide technical guidance to team members.
• Bachelor's degree in Computer Science, Computer Engineering, Information Technology, or a related field.
• 3+ years of experience building and maintaining data pipelines.
• Proficiency in SQL and experience with relational databases (Oracle, SQL Server) including performance tuning and query optimization.
• Hands-on experience with ETL tools such as SSIS, Talend, and PySpark, and data modeling for OLAP solutions using SSAS.
• Knowledge of data pipeline orchestration using Apache Airflow.
• Experience with big data processing frameworks such as Apache Spark for distributed data transformations.
• Hands-on experience with cloud database/data platform services such as AWS Redshift, S3, and ClickHouse.
• Solid understanding of data warehousing concepts, star/snowflake schema, and partitioning strategies for large datasets (300M+ rows).
• Familiarity with insurance industry data or other regulated environments (preferred).
• Proficiency in Python or another scripting language for automation and data manipulation.
• Knowledge of data quality, governance, and security best practices.
• Ability to work with large-scale data and optimize workflows for performance and scalability.
• Preferred Qualifications.
• Experience with Power BI and building efficient data marts.
• Experience with data privacy, governance, and secure data access practices.
• Hands-on with cloud platforms or tools such as AWS (Redshift, S3), ClickHouse, Azure, Databricks, Delta Lake, Snowflake, or Hadoop ecosystem.
• Able to troubleshoot performance issues in both backend pipelines and frontend analytics tools.
• Comfortable working in a fast-paced, high-ownership environment with cross-functional teams.

ประสบการณ์:

5 ปีขึ้นไป

ทักษะ:

Problem Solving, Architecture, Automation, Big Data, Python, Apache, Kafka, Scala, SQL, ETL

ประเภทงาน:

งานประจำ

• We are looking for a visionary and technical.
• Lead Data Engineer.
• to guide and scale our data engineering team within our regional data chapter. In this role, you will own the architecture, evolution, and reliability of our next-generation regional data platform. You will lead a talented team of engineers to optimize our.
• Databricks-driven Data Lakehouse architecture., drive core DataOps practices, implement robust data governance, and collaborate across functional squads to empower advanced analytics, business intelligence, and AI initiatives.
• The ideal candidate is an expert data architect and a proven technical leader who thrives on transforming messy, disconnected datasets into a unified, low-latency, and highly secure data ecosystem.
• Design, build, and continuously optimize our scalable Data Lakehouse platform leveraging Databricks and AWS infrastructure to support global business expansion.
• Lead the design and implementation of highly automated, optimal real-time and batch data extraction, transformation, and loading (ETL/ELT) frameworks. Oversee complex integration with internal microservices, external insurance partners, and third-party APIs.
• Champion engineering best practices by building framework controls, schema registries, automated testing, and CI/CD pipelines for data assets (utilizing tools like dbt and Airflow). Drive initiatives like Databricks serverless migrations and automated performance monitoring.
• Own the end-to-end framework for regional data quality, data observability (e.g., Elementary), data freshness, and data catalogs. Ensure robust data security, compliance (PDPA), and sensitivity tagging across multi-region boundaries.
• Partner with Executives, Product Owners, Software Developers, Data Analysts, and MLOps/Data Science squads to unblock complex technical dependencies, align infrastructure capabilities, and deliver actionable data products.
• Actively research and spearhead proof-of-concepts incorporating advanced technologies like Generative AI/Agentic AI data pipelines (e.g., automated knowledge bases, smart web scraping solutions) into the data ecosystem.
• Manage, mentor, and elevate the technical capabilities of junior and senior data engineers within regional squads, ensuring standardized practices and strong technical ownership.
• 5+ years of experience in Data Engineering, Data Architecture, or a related technical capability role, with at least 2+ years leading engineering teams or core technical projects.
• Deep hands-on experience designing and managing production workloads in.
• Databricks.
• (Delta Lake, Unity Catalog, and serverless compute paradigms).
• Master-level proficiency in.
• SQL.
• (complex query authoring, optimization, and macro writing) and programmatic data engineering in.
• Python.
• or.
• Scala.
• Heavy experience with Big Data open-source frameworks, primarily.
• Apache Spark.
• Expertise with modern cloud data pipeline orchestration tools (e.g.,.
• Airflow., Dagster) and transformation tools like.
• dbt.
• Solid mastery over.
• AWS cloud services.
• infrastructure (S3, EC2, RDS, VPC configurations, network connectivity) integrated within data ecosystems.
• Expert knowledge of transactional databases, distributed storage, message queuing/streaming (e.g., Kafka), and structural patterns for Lakehouse data modeling (Medallion architecture: Bronze, Silver, Gold layers).
• Proven experience performing root cause analysis on production infrastructure failures, handling complex code/infrastructure migrations, and managing data pipeline debts (e.g., optimizing small file storage).
• Bachelor's or Master's degree in Computer Science, Computer Engineering, Information Technology, or a highly quantitative relevant field.

ทักษะ:

System Administration, ElasticSearch, Architecture, Automation, Kubernetes, MongoDB, Python, Docker, DevOps, Apache, Kafka, Redis, Linux, English, Thai

ประเภทงาน:

งานประจำ

• Design, develop, operate, and manage scalable, resilient, and secure Technology Automation Platforms.
• Build, maintain, and optimize hybrid infrastructure environments across cloud and on-premises platforms.
• Develop and manage Infrastructure-as-Code (IaC) solutions to automate platform provisioning, secure software deployment, and operational processes through CI/CD pipelines.
• Ensure platform availability, performance, reliability, and disaster recovery readiness.
• Automate infrastructure deployment, configuration management, monitoring, patch management, upgrades, and security compliance activities.
• Support release management, deployment automation, and production implementation activities.
• Perform root cause analysis, incident management, troubleshooting, and resolution of complex infrastructure and platform issues.
• Design and implement monitoring, logging, observability, and operational excellence solutions.
• Develop recommendations, roadmaps, and implementation plans to enhance platform stability, security, scalability, and efficiency.
• Partner with development, security, architecture, and operations teams to support platform modernization initiatives and cloud transformation programs.
• Contribute technical guidance and best practices while mentoring junior engineers and team members where appropriate.
• You are a highly motivated technology professional with strong experience in platform engineering, infrastructure automation, cloud technologies, and DevOps practices. You possess a growth mindset, enjoy solving complex technical challenges, and are passionate about improving operational efficiency through automation and innovation.
• You thrive in fast-paced enterprise environments and are comfortable working with cross-functional teams across different cultures and geographies. You combine deep technical expertise with strong communication skills and a customer-first approach.
• Your Future at Kyndryl.
• Every position at Kyndryl offers a way forward to grow your career. We have opportunities that you won't find anywhere else, including hands-on experience, learning opportunities, and the chance to certify in all four major platforms. Whether you want to broaden your knowledge base or narrow your scope and specialize in a specific sector, you can find your opportunity here.
• Who You Are.
• You're good at what you do and possess the required experience to prove it. However, equally as important - you have a growth mindset; keen to drive your own personal and professional development. You are customer-focused - someone who prioritizes customer success in their work. And finally, you're open and borderless - naturally inclusive in how you work with others.
• Required Technical and Professional Expertise.
• Linux or Windows System Administration.
• Middleware Administration.
• Cloud Infrastructure.
• DevOps Engineering.
• Container Platforms.
• Infrastructure Automation.
• Experience supporting enterprise-scale or mission-critical production environments.
• MongoDB.
• Redis.
• PostgreSQL.
• Apache Kafka.
• Elasticsearch.
• Loki.
• OpenTelemetry.
• HashiCorp Vault.
• Apache Tomcat.
• ArgoCD.
• Ansible.
• AWS Cloud.
• Terraform.
• API technologies and integration.
• Ansible Playbooks.
• Bash.
• PowerShell.
• Python.
• Experience designing and managing CI/CD pipelines and Infrastructure-as-Code solutions.
• Strong knowledge of cloud-native architecture, implementation, and operational support, with experience in AWS Cloud preferred.
• Strong analytical, troubleshooting, and problem-solving skills.
• Excellent verbal and written communication skills in both Thai and English.
• Ability to work effectively in multicultural and high-pressure environments.
• Preferred Technical and Professional Experience.
• Experience within Banking, Financial Services, Insurance (BFSI), or other highly regulated enterprise environments.
• Experience with containerization and orchestration technologies such as Docker, Kubernetes, or OpenShift.
• Knowledge of Site Reliability Engineering (SRE) practices, observability frameworks, and platform security controls.
• Experience supporting AI-enabled cloud-native platforms and related infrastructure services.
• Bachelor's degree in Computer Science, Information Technology, Engineering, or a related discipline.
• Relevant certifications in AWS, Terraform, DevOps, Cloud, or Infrastructure Automation technologies.
• Being You.
• The "Kyn" in Kyndryl means kinship, which represents the strong bonds we have with each other, our customers and our communities. We focus on ensuring all Kyndryls feel included and we welcome people of all cultures, backgrounds, and experiences. Even if you don't meet every requirement, we encourage you to apply. We believe in growth, and we're excited to see what you can bring. At Kyndryl, employee feedback has told us that our number one driver of employee engagement is belonging. That sense of belonging being a valued, respected, trusted member of the team is fundamental to our culture and fueling great experiences for our customers. This dedication to welcoming everyone into our company means that Kyndryl gives you the ability to thrive and contribute to our culture of empathy and shared success. That's The Kyndryl Way.
• What You Can Expect.
• Your career with us isn't just a job it's an adventure with purpose. We offer a dynamic, hybrid-friendly culture that supports your well-being and empowers you to grow. Our Be Well programs are thoughtfully designed to support your financial, mental, physical, and social health because we know that when you feel your best, you do your best.
• From your very first day, you'll dive into impactful work that powers the systems our customers rely on every day. You won't just contribute you'll make a difference, tackling meaningful projects that sharpen your skills and fuel your growth.
• We're here to champion your journey. With powerful tools to chart your career path, personalized development goals aligned with your ambitions, and continuous feedback to keep you inspired and on track, you'll have everything you need to thrive and evolve. You'll develop in-demand skills to grow your career and achieve your ambitions with access to cutting-edge learning opportunities from certifications with Microsoft, Google, and Amazon to coaching and hands-on experiences. And through it all, you'll be part of a culture that values empathy, restless learning, and a devotion to shared success.
• We want you to thrive here and we're committed to helping you do just that. Ready to make an impact? Join us and help shape what's next.
• Get Referred!.
• If you know someone that works at Kyndryl, when asked 'How Did You Hear About Us' during the application process, select 'Employee Referral' and enter your contact's Kyndryl email address.

ทักษะ:

Software Development, Financial Reporting, Agile Development, Architecture, Recruitment, Kubernetes, Big Data, YouTube, Kotlin, Hadoop, Apache, Kafka, Scala, Scrum, Java, SQL, English

ประเภทงาน:

งานประจำ

• At Agoda, we bridge the world through travel. Our story began in 2005, when two lifelong friends and entrepreneurs, driven by their passion for travel, launched Agoda to make it easier for everyone to explore the world.
• Today, we are part of Booking Holdings [NASDAQ: BKNG], with a diverse team of over 7,000 people from 90 countries, working together in offices around the globe. Every day, we connect people to destinations and experiences, with our great deals across our millions of hotels and holiday properties, flights, and experiences worldwide.
• No two days are the same at Agoda. Data and technology are at the heart of our culture, fueling our curiosity and innovation. If you're ready to begin your best journey and help build travel for the world, join us.
• Fintech is one of the fastest growing areas in Agoda and we are rapidly expanding our tech team. We work closely with the finance business team and our Fintech product owners to reduce risk, drive efficiencies and move on new market opportunities in this exciting field. We have a wide range of projects from traditional finance to cutting-edge customer fintech. For example, reconciliation using Big Data technologies, growing and optimizing customer payments options, tax calculations in milli-second.
• r.
• esponse.
• times and a mesh of supplier payment options like virtual credit cards. It.
• s a hot field and the perfect mix of data engineering and backend engineering.
• The Opportunity.
• In this role, you will not only develop robust backend systems but also architect and maintain scalable data pipelines and storage solutions that support complex data collection, processing, and analysis. Your dual expertise in backend and data engineering will play a crucial role in optimizing our financial technology solutions and driving informed business decisions through reliable data insights.
• In This Role, You'll Get to.
• Think and own the full life cycle of our products, not just a single piece of code - from business requirements, technology selection, coding standards, agile development, unit and application testing, to CI/CD and proper monitoring.
• Design, develop and maintain platforms and data pipelines across fintech.
• Boost System Performance: build systems that are stable, scalable, and highly performant to meet the dynamic demands of the financial landscape.
• Write great code and help others write great code - mentor people in your team and wider.
• Collaborate with other teams and departments.
• Exceptional problem-solving skills coupled with a strategic mindset are essential. You possess the ability to adapt to new changes and the foresight to anticipate future needs. Leadership at Agoda isn't just managing tasks but inspiring innovation and driving vision into reality.
• Foster Cross-Functional Collaboration: work with diverse teams to drive forward product and technology goals.
• Shape our future team: Play a pivotal role in recruiting and onboarding exceptional talent.
• What You'll Need to Succeed.
• 8+ years.
• of experience with strong proficiency in Java, Kotlin, Scala with a proven track record of developing high-performance applications in production settings. Insightful experience with big data technologies like Hadoop, real-time processing frameworks (e.g., Apache Spark), and advanced knowledge of SQL and data architecture.
• Thinks in systems: their edge cases, failure modes, and life cycles.
• Uses a metrics driven approach and can make informed decisions using data.
• You are passionate about the craft of software development and constantly work to improve your knowledge and skills.
• Experience with Scrum/Agile development methodologies.
• Excellent verbal and written English communication skills.
• Experience with operational excellence and a deep understanding of metrics, alarms and dashboards.
• It's Great If You Have.
• Experience working in a modern FinTech or Payments organization.
• Domain knowledge in any of these areas: financial reconciliation, financial reporting, tax, payout methods like virtual credit cards or customer payments.
• Hands-on experience working with technologies like Spark for data processing, ETLs for data pipelines and queueing systems (Kafka, RabbitMQ).
• Core engineering infrastructure tools like GitLab for source control and Continuous Integration, Kubernetes.
• Experience developing, maintaining and debugging large-scale distributed systems.
• Experience in leading projects, initiatives and/or teams, with full ownership of the systems involved.
• This position is based in Bangkok, Thailand (Relocation Provided).
• Bengaluru.
• Please review our Hiring Process Guidelines before your interview click.
• here.
• to learn how interviewing at Agoda works.
• Discover more about working at Agoda.
• Agoda Careers.
• https://careersatagoda.com.
• Facebook.
• https://www.facebook.com/agodacareers/.
• LinkedIn.
• https://www.linkedin.com/company/agoda.
• YouTube.
• https://www.youtube.com/agodalife.
• Equal Opportunity Employer.
• At Agoda, we pride ourselves on being a company represented by people of all different backgrounds and orientations. We prioritize attracting diverse talent and cultivating an inclusive environment that encourages collaboration and innovation. Employment at Agoda is based solely on a person's merit and qualifications. We are committed to providing equal employment opportunity regardless of sex, age, race, color, national origin, religion, marital status, pregnancy, sexual orientation, gender identity, disability, citizenship, veteran or military status, and other legally protected characteristics.
• We will keep your application on file so that we can consider you for future vacancies and you can always ask to have your details removed from the file. For more details please read our.
• privacy policy.
• Disclaimer.
• We do not accept any terms or conditions, nor do we recognize any agency's representation of a candidate, from unsolicited third-party or agency submissions. If we receive unsolicited or speculative CVs, we reserve the right to contact and hire the candidate directly without any obligation to pay a recruitment fee.

ประสบการณ์:

7 ปีขึ้นไป

ทักษะ:

MongoDB, Python, Hadoop, Apache, MySQL, Thai

ประเภทงาน:

งานประจำ

• About LINE MAN Wongnai.
• LINE MAN Wongnai is Thailand's Leading On-Demand Delivery and Lifestyle e-Commerce platform services. We build technology to help Thai people live better, to empower all local businesses by creating an end-to-end food ecosystem through our channel LINE MAN and Wongnai. Connected consumers, riders, and local businesses and improved the daily life of all parties with restaurants nationwide. And because we are local, we provide the deepest variety and services that are tailor-made for Thai people.
• We are looking for an experienced data lead to develop large and high performance data processing systems to drive our business growth. Working in a fast-paced environment, you will bring your expertise and skills to tackle the challenges that impact millions of people on our journey to become the No.1 food platform in Thailand.
• Design and develop large and high performance data processing systems to drive LINE MAN Wongnai business growth and improve the product experience.
• Lead and oversee data engineering projects to ensure pipelines are reliable, efficient, testable, & maintainable.
• Improve data quality to management and governance.
• Evangelize high quality software engineering practices towards building data pipelines and platforms at scale.
• Contribute to shared engineering tooling & standards to improve the productivity and quality of output for engineers across the company.
• At least 3-7 years of practical or hands-on experience in Data Engineering or relevant industry.
• Excellent problem-solving skills and attention to detail.
• Effective communication and collaboration skills.
• Knowledge and experience with data quality frameworks (e.g., Great Expectations).
• Working knowledge with both relational and non-relational databases (e.g., MongoDB, MySQL, PostgreSQL).
• Strong proficiency in SQL, Python, and other programming languages commonly used in data engineering.
• Extensive hands-on experience with Apache Spark Batch/Real Time and performance tuning.
• Proven hands-on experience with Hadoop and familiarity with open table formats.
• Experience with Polars and DuckDB (Preferable).

ทักษะ:

Architecture, Python, Apache, Kafka, SQL, ETL

ประเภทงาน:

งานประจำ

• Data Engineer is responsible for handling the design and construction of scalable data management system including data storage, data piping, ETL and interfacing with analytics platforms. The jobholder needs to manage all data aspects related to public cloud solution, data lake, data warehouse, reporting, etc. The job holder is also required to participate in gathering data requirements, modelling, and testing as well as define flow of data in a project from input through to storage including interfaces with analytics tools or end user software.
• Key Accountabilities.
• Providing technical guidance related to data architecture, data models and meta data management to IT function and imitative leaders.
• Define and implement data flows through/ and around digital products.
• Participate in data modeling and testing to ensure smooth operations.
• Extract relevant data to solve analytical problems, and ensure development teams have the required data.
• Interact with the initiative leaders to understand all data requirements used for business insights development, and translates into data structures and data model requirements to IT function.
• Develop set processes for data profiling, data quality, data transformation, data mining and data protection.
• Work closely with database teams on topics related to data requirements, cleanliness, accuracy, and etc.,.
• Track analytics impact on business, and provide recommendation for better result.
• Monitor market watch, and provide recommendation to improve efficiency of current projects.
• Professional Knowledge & Experiences.
• Bachelor's Degree in computer science, statistics, or related technical discipline.
• 5+ years' experience with advanced data management system and master data management.
• Experience in developing applications in high volume data staging/ ETL environments and proficient in advanced SQL skills, Python programming and familiar with pandas scikit-learn, matplotlib, numpy, dash library.
• Experience in using Data Analytics products such as BigQuery, Apache Kafka, Apache Airflow, Cloud Storage, etc.
• Clear understanding in different data domains of operations, customers, etc.
• Ability to quickly learn new technologies.
• Additional Desirable Qualification.
• CORE Competencies.

ประสบการณ์:

5 ปีขึ้นไป

ทักษะ:

Software Development, Automation, Oracle, Apache, VMware, Linux, SQL, GIS

ประเภทงาน:

งานประจำ

• Lead, mentor, and manage the Application Support squad (3 Junior engineers), ensuring high morale, optimal performance, and continuous skill development.
• Design and maintain the Shift Roster (Onshore/Offshore Day Shifts and Night Batch Specialist Shifts) with clear daily handover checklists to guarantee 24/7 coverage.
• Establish and govern clear Service Demarcation Lines and handoff points between App Support, Helpdesk, Software Development,SRE and Server teams, eliminating duplicate efforts.
• Manage the implementation and optimization of ITSM, ensuring robust processes for Incident, Problem, Change and Service Request modules.
• Partner with the Bank's IT team to implement API-level Ticket Bridging maintaining a target ticket assignment accuracy of >90%.
• Serve as the primary escalation point for application issues; cooperate with Incident Manager and Technical Teams in the "War Room" during P1/P2 incidents to rapidly restore systems and achieve SLA targets (Downtime 90%.
• Serve as the primary escalation point for application issues; cooperate with Incident Manager and Technical Teams in the "War Room" during P1/P2 incidents to rapidly restore systems and achieve SLA targets (Downtime < 4.32 mins/month).
• Specific knowledge and skill / ความรู้เฉพาะตำแหน่ง.
• System & Application Knowledge: Familiarity with core financial systems (CIS, ESS, SBL, MFET, GIS, SAXO, Front IFIS).
• Tech Stack Literacy: Good understanding of Windows/Linux servers, Active Directory, VMware virtualization, SQL databases (MSSQL, Oracle and Postgre), SFTP protocols, GoAnywhere, Apache Aitflow,.
• Core ITSM Administration: ITSM configuration, ticket routing rules, and API integrations.
• Operations & Batch Control: Knowledge of Batch scheduling, automation tools, and transaction logs processing.
• Analytical Skills: Root Cause Analysis (RCA) and Incident Trend analysis.
• Apply now ".

ประสบการณ์:

3 ปีขึ้นไป

ทักษะ:

Microsoft Azure, Python, Apache, Kafka, SQL

ประเภทงาน:

งานประจำ

• You have hands-on experience delivering end-to-end data solutions and a strong foundation in areas such as large-scale data processing, data infrastructure engineering, or data modeling.
• You are proficient in Python and SQL, and apply solid engineering practices including testing, version control, CI/CD, and writing maintainable code.
• You have strong, practical experience with Databricks and Apache Spark, and are capable of building, optimizing, and operating production-grade data pipelines.
• You have experience working with streaming data or event-driven pipelines using Kafka or similar technologies.
• You are familiar with workflow orchestration using tools like Airflow, Azure Data Factory, or similar platforms for scheduling, monitoring, and managing data pipelines.
• You have experience working with cloud-based data platforms, particularly on Microsoft Azure; exposure to AWS is a plus.
• You collaborate effectively across teams, communicate clearly, and use strong data intuition to design valuable analytical or operational solutions.
• You are curious, resilient, and thoughtful comfortable learning new technologies, embracing feedback, and improving how things are done.

ประสบการณ์:

2 ปีขึ้นไป

ทักษะ:

Architecture, Automation, Backbone, Python, DevOps, Apache, SQL, ETL

ประเภทงาน:

งานประจำ

• At Gosoft, were the tech powerhouse behind CP ALL Grouppowering innovations for over 15,000 7-Eleven stores nationwide, including platforms like 7-Delivery. As part of our Data Science & Data Engineering team, youll work at the cutting edge of cloud-native tech and big dataespecially on Databricks Lakehouse and AWS/GCP.
• Were looking for passionate engineers ready to build high-impact data systems that shape the future of retail.
• Design and maintain scalable data pipelines on Databricks Lakehouse Platform.
• Build ETL/ELT workflows for both structured and unstructured data.
• Partner with data scientists and analysts to turn raw data into actionable insights.
• Optimize performance of Spark jobs, Delta Lake, and streaming pipelines.
• Lead platform monitoring, CI/CD automation, and cloud-native governance.
• Apply best practices in data security, quality, and governance.
• What Were Looking For.
• Degree in Computer Science, Engineering, or related field.
• 2+ years of hands-on experience in Data Engineering / Platform Engineering.
• Strong with Databricks, Apache Spark, Delta Lake.
• Skilled in Python, SQL, and working in notebooks (Jupyter/Databricks).
• Experience in AWS or GCP services.
• Solid understanding of Lakehouse Architecture and Data Modeling.
• Familiar with CI/CD, Git, and MLOps/DevOps for data platforms.
• Bonus: Experience in retail tech, data privacy, and RBAC.
• Why Gosoft?.
• Impact: Be the backbone of the data powering 7-Elevens national operations.
• Innovation: Work on modern architecture and enterprise-scale platforms.
• Growth: Learn from top talent in DataOps, MLOps, and Cloud Engineering.
• Flexibility: Hybrid working, continuous learning, and career advancement.

ประสบการณ์:

7 ปีขึ้นไป

ทักษะ:

Software Development, Financial Reporting, Agile Development, Architecture, Recruitment, Kubernetes, Big Data, YouTube, Kotlin, Hadoop, Apache, Kafka, Scala, Scrum, Java, SQL, English

ประเภทงาน:

งานประจำ

• At Agoda, we bridge the world through travel. Our story began in 2005, when two lifelong friends and entrepreneurs, driven by their passion for travel, launched Agoda to make it easier for everyone to explore the world.
• Today, we are part of Booking Holdings [NASDAQ: BKNG], with a diverse team of over 7,000 people from 90 countries, working together in offices around the globe. Every day, we connect people to destinations and experiences, with our great deals across our millions of hotels and holiday properties, flights, and experiences worldwide.
• No two days are the same at Agoda. Data and technology are at the heart of our culture, fueling our curiosity and innovation. If you're ready to begin your best journey and help build travel for the world, join us.
• Fintech is one of the fastest growing areas in Agoda and we are rapidly expanding our tech team. We work closely with the finance business team and our Fintech product owners to reduce risk, drive efficiencies and move on new market opportunities in this exciting field. We have a wide range of projects from traditional finance to cutting-edge customer fintech. For example, reconciliation using Big Data technologies, growing and optimizing customer payments options, tax calculations in milli-second.
• r.
• esponse.
• times and a mesh of supplier payment options like virtual credit cards. It.
• s a hot field and the perfect mix of data engineering and backend engineering.
• The Opportunity.
• In this role, you will not only develop robust backend systems but also architect and maintain scalable data pipelines and storage solutions that support complex data collection, processing, and analysis. Your dual expertise in backend and data engineering will play a crucial role in optimizing our financial technology solutions and driving informed business decisions through reliable data insights.
• In This Role, You'll Get to.
• Think and own the full life cycle of our products, not just a single piece of code - from business requirements, technology selection, coding standards, agile development, unit and application testing, to CI/CD and proper monitoring.
• Design, develop and maintain platforms and data pipelines across fintech.
• Boost System Performance: build systems that are stable, scalable, and highly performant to meet the dynamic demands of the financial landscape.
• Write great code and help others write great code - mentor people in your team and wider.
• Collaborate with other teams and departments.
• Exceptional problem-solving skills coupled with a strategic mindset are essential. You possess the ability to adapt to new changes and the foresight to anticipate future needs. Leadership at Agoda isn't just managing tasks but inspiring innovation and driving vision into reality.
• Foster Cross-Functional Collaboration: work with diverse teams to drive forward product and technology goals.
• Shape our future team: Play a pivotal role in recruiting and onboarding exceptional talent.
• What You'll Need to Succeed.
• 8+ years.
• of experience with strong proficiency in Java, Kotlin, Scala with a proven track record of developing high-performance applications in production settings. Insightful experience with big data technologies like Hadoop, real-time processing frameworks (e.g., Apache Spark), and advanced knowledge of SQL and data architecture.
• Thinks in systems: their edge cases, failure modes, and life cycles.
• Uses a metrics driven approach and can make informed decisions using data.
• You are passionate about the craft of software development and constantly work to improve your knowledge and skills.
• Experience with Scrum/Agile development methodologies.
• Excellent verbal and written English communication skills.
• Experience with operational excellence and a deep understanding of metrics, alarms and dashboards.
• It's Great If You Have.
• Experience working in a modern FinTech or Payments organization.
• Domain knowledge in any of these areas: financial reconciliation, financial reporting, tax, payout methods like virtual credit cards or customer payments.
• Hands-on experience working with technologies like Spark for data processing, ETLs for data pipelines and queueing systems (Kafka, RabbitMQ).
• Core engineering infrastructure tools like GitLab for source control and Continuous Integration, Kubernetes.
• Experience developing, maintaining and debugging large-scale distributed systems.
• Experience in leading projects, initiatives and/or teams, with full ownership of the systems involved.
• This position is based in Bangkok, Thailand (Relocation Provided).
• Bengaluru.
• Please review our Hiring Process Guidelines before your interview click.
• here.
• to learn how interviewing at Agoda works.
• Discover more about working at Agoda.
• Agoda Careers.
• https://careersatagoda.com.
• Facebook.
• https://www.facebook.com/agodacareers/.
• LinkedIn.
• https://www.linkedin.com/company/agoda.
• YouTube.
• https://www.youtube.com/agodalife.
• Equal Opportunity Employer.
• At Agoda, we pride ourselves on being a company represented by people of all different backgrounds and orientations. We prioritize attracting diverse talent and cultivating an inclusive environment that encourages collaboration and innovation. Employment at Agoda is based solely on a person's merit and qualifications. We are committed to providing equal employment opportunity regardless of sex, age, race, color, national origin, religion, marital status, pregnancy, sexual orientation, gender identity, disability, citizenship, veteran or military status, and other legally protected characteristics.
• We will keep your application on file so that we can consider you for future vacancies and you can always ask to have your details removed from the file. For more details please read our.
• privacy policy.
• Disclaimer.
• We do not accept any terms or conditions, nor do we recognize any agency's representation of a candidate, from unsolicited third-party or agency submissions. If we receive unsolicited or speculative CVs, we reserve the right to contact and hire the candidate directly without any obligation to pay a recruitment fee.

ทักษะ:

Software Development, Financial Reporting, Agile Development, Architecture, Recruitment, Kubernetes, Big Data, YouTube, Kotlin, Hadoop, Apache, Kafka, Scala, Scrum, Java, SQL, C#, English

ประเภทงาน:

งานประจำ

• At Agoda, we bridge the world through travel. Our story began in 2005, when two lifelong friends and entrepreneurs, driven by their passion for travel, launched Agoda to make it easier for everyone to explore the world.
• Today, we are part of Booking Holdings [NASDAQ: BKNG], with a diverse team of over 7,000 people from 90 countries, working together in offices around the globe. Every day, we connect people to destinations and experiences, with our great deals across our millions of hotels and holiday properties, flights, and experiences worldwide.
• No two days are the same at Agoda. Data and technology are at the heart of our culture, fueling our curiosity and innovation. If you're ready to begin your best journey and help build travel for the world, join us.
• Fintech is one of the fastest growing areas in Agoda and we are rapidly expanding our tech team. We work closely with the finance business team and our Fintech product owners to reduce risk, drive efficiencies and move on new market opportunities in this exciting field. We have a wide range of projects from traditional finance to cutting-edge customer fintech. For example, reconciliation using Big Data technologies, growing and optimizing customer payments options, tax calculations in milli-second.
• response.
• times and a mesh of supplier payment options like virtual credit cards. It.
• s a hot field and the perfect mix of data engineering and backend engineering.
• The Opportunity.
• In this role, you will not only develop robust backend systems but also architect and maintain scalable data pipelines and storage solutions that support complex data collection, processing, and analysis. Your dual expertise in backend and data engineering will play a crucial role in optimizing our financial technology solutions and driving informed business decisions through reliable data insights.
• In This Role, You'll Get to.
• Think and own the full life cycle of our products, not just a single piece of code - from business requirements, technology selection, coding standards, agile development, unit and application testing, to CI/CD and proper monitoring.
• Design, develop and maintain platforms and data pipelines across fintech.
• Boost System Performance: build systems that are stable, scalable, and highly performant to meet the dynamic demands of the financial landscape.
• Write great code and help others write great code - mentor people in your team and wider.
• Collaborate with other teams and departments.
• Exceptional problem-solving skills coupled with a strategic mindset are essential. You possess the ability to adapt to new changes and the foresight to anticipate future needs. Leadership at Agoda isn't just managing tasks but inspiring innovation and driving vision into reality.
• Foster Cross-Functional Collaboration: work with diverse teams to drive forward product and technology goals.
• Shape our future team: Play a pivotal role in recruiting and onboarding exceptional talent.
• What You'll Need to Succeed.
• 10+ years.
• of experience with strong proficiency in.
• Java, Kotlin, Scala, or C#.
• with a proven track record of developing high-performance applications in production settings. Insightful experience with big data technologies like Hadoop, real-time processing frameworks (e.g., Apache Spark), and advanced knowledge of SQL and data architecture.
• Thinks in systems: their edge cases, failure modes, and life cycles.
• Uses a metrics driven approach and can make informed decisions using data.
• You are passionate about the craft of software development and constantly work to improve your knowledge and skills.
• Experience with Scrum/Agile development methodologies.
• Excellent verbal and written English communication skills.
• Experience with operational excellence and a deep understanding of metrics, alarms and dashboards.
• It's Great If You Have.
• Experience working in a modern FinTech or Payments organization.
• Domain knowledge in any of these areas: financial reconciliation, financial reporting, tax, payout methods like virtual credit cards or customer payments.
• Hands-on experience working with technologies like Spark for data processing, ETLs for data pipelines and queueing systems (Kafka, RabbitMQ).
• Core engineering infrastructure tools like GitLab for source control and Continuous Integration, Kubernetes.
• Experience developing, maintaining and debugging large-scale distributed systems.
• Experience in leading projects, initiatives and/or teams, with full ownership of the systems involved.
• This position is based in Bangkok, Thailand. (Relocation package is provided).
• Bengaluru.
• SaoPaulo.
• Please review our Hiring Process Guidelines before your interview click.
• here.
• to learn how interviewing at Agoda works.
• Discover more about working at Agoda.
• Agoda Careers.
• https://careersatagoda.com.
• Facebook.
• https://www.facebook.com/agodacareers/.
• LinkedIn.
• https://www.linkedin.com/company/agoda.
• YouTube.
• https://www.youtube.com/agodalife.
• Equal Opportunity Employer.
• At Agoda, we pride ourselves on being a company represented by people of all different backgrounds and orientations. We prioritize attracting diverse talent and cultivating an inclusive environment that encourages collaboration and innovation. Employment at Agoda is based solely on a person's merit and qualifications. We are committed to providing equal employment opportunity regardless of sex, age, race, color, national origin, religion, marital status, pregnancy, sexual orientation, gender identity, disability, citizenship, veteran or military status, and other legally protected characteristics.
• We will keep your application on file so that we can consider you for future vacancies and you can always ask to have your details removed from the file. For more details please read our.
• privacy policy.
• Disclaimer.
• We do not accept any terms or conditions, nor do we recognize any agency's representation of a candidate, from unsolicited third-party or agency submissions. If we receive unsolicited or speculative CVs, we reserve the right to contact and hire the candidate directly without any obligation to pay a recruitment fee.

ทักษะ:

Kafka, Redis, Automation, English

ประเภทงาน:

งานประจำ

• Design and review middleware architecture aligned with enterprise standards.
• Manage and govern middleware platforms (Web Server, App Server, MQ, Kafka, Redis).
• Oversee outsourcing/vendor teams and coordinate project delivery.
• Improve CI/CD deployment pipelines and automation.
• Monitor system performance, conduct root cause analysis (RCA).
• Manage lifecycle activities (capacity, patching, upgrades, EOS/EOL).
• Ensure system stability, security, and compliance with IT standards.
• QualificationsBachelor s degree in Computer Science, IT, Engineering, or related field.
• Hands-on in middleware (IBM MQ, Kafka).
• Experience with Web/App Servers (Apache, Nginx, Tomcat, JBoss, WebSphere, IIS).
• Familiar with Redis, Linux, Docker, Kubernetes.
• Exposure to monitoring tools and CI/CD.
• Middleware architecture & performance tuning.
• Analytical problem-solving.
• Good communication & English.
• Only shortlisted candidates will be contacted.
• Talent Acquisition Department
• Bank of Ayudhya Public Company Limited
• 1222 Rama III Rd., Bangpongpang, Yannawa, Bangkok 10120
• Contact: Talent Acquisition Center: 0 2--- ---- #--183.
• FB: Krungsri Career.
• LINE: Krungsri Career.
• LINKEDIN: Krungsri.
• Applicants can read the Personal Data Protection Announcement of the Bank's Human Resources Function by typing the link from the image that stated below.
• EN (https://krungsri.com/b/privacynoticeen).
• ผู้สมัครสามารถอ่านประกาศการคุ้มครองข้อมูลส่วนบุคคลส่วนงานทรัพยากรบุคคลของธนาคารได้โดยการพิมพ์ลิงค์จากรูปภาพที่ปรากฎด้านล่าง.
• ภาษาไทย (https://krungsri.com/b/privacynoticeth).
• หมายเหตุ ธนาคารมีความจำเป็นและจะมีขั้นตอนการตรวจสอบข้อมูลส่วนบุคคลเกี่ยวกับประวัติอาชญากรรมของผู้สมัคร ก่อนที่ผู้สมัครจะได้รับการพิจารณาเข้าร่วมงานกับธนาคารกรุงศรีฯ.
• Remark: The bank needs to and will have a process for verifying personal information related to the criminal history of applicants before they are considered for employment with the bank.

ทักษะ:

Automation

ประเภทงาน:

งานประจำ

• Operate, manage, and optimize scalable, resilient, and secure Technology Automation Platforms.
• Build, maintain, and support hybrid infrastructure environments across on-premises and cloud platforms.
• Design, develop, and manage Infrastructure-as-Code (IaC) solutions using automation tools and CI/CD pipelines.
• Ensure platform availability, reliability, performance, security, and disaster recovery readiness.
• Automate infrastructure provisioning, configuration management, monitoring, patching, upgrades, and security controls.
• Support application release management and production deployment activities.
• Perform incident investigation, root cause analysis, troubleshooting, and problem resolution for infrastructure and platform-related issues.
• Collaborate closely with development, operations, security, and engineering teams to continuously improve platform capabilities and operational efficiency.
• Implement monitoring, observability, and logging solutions to ensure system health and performance.
• Contribute to platform modernization initiatives and adoption of DevOps best practices.
• Your Future at Kyndryl.
• Every position at Kyndryl offers a way forward to grow your career. We have opportunities that you won't find anywhere else, including hands-on experience, learning opportunities, and the chance to certify in all four major platforms. Whether you want to broaden your knowledge base or narrow your scope and specialize in a specific sector, you can find your opportunity here.
• Who You Are.
• You're good at what you do and possess the required experience to prove it. However, equally as important - you have a growth mindset; keen to drive your own personal and professional development. You are customer-focused - someone who prioritizes customer success in their work. And finally, you're open and borderless - naturally inclusive in how you work with others.
• Required Technical and Professional Expertise.
• Linux or Windows System Administration.
• Middleware Administration.
• Cloud Infrastructure.
• DevOps Engineering.
• Container Platforms.
• Infrastructure Automation.
• Experience supporting enterprise-scale or mission-critical production environments.
• Strong understanding of automation, CI/CD practices, and Infrastructure-as-Code methodologies.
• MongoDB.
• Redis.
• PostgreSQL.
• Apache Kafka.
• Elasticsearch.
• Loki.
• OpenTelemetry.
• HashiCorp Vault.
• Apache Tomcat.
• ArgoCD.
• Ansible.
• AWS Cloud Services.
• Terraform.
• API Integration and Management.
• Experience with monitoring, logging, observability, and performance tuning.
• Strong troubleshooting and analytical problem-solving skills.
• Ability to work effectively in a multicultural, high-pressure environment.
• Fluent communication skills in Thai and English.
• Preferred Technical and Professional Experience.
• Experience in Banking, Financial Services, Insurance (BFSI), or other highly regulated enterprise environments.
• Experience with Kubernetes, OpenShift, Docker, or container orchestration platforms.
• Knowledge of security best practices, disaster recovery, and high-availability architectures.
• Relevant cloud, DevOps, or infrastructure certifications are advantageous.
• Being You.
• The "Kyn" in Kyndryl means kinship, which represents the strong bonds we have with each other, our customers and our communities. We focus on ensuring all Kyndryls feel included and we welcome people of all cultures, backgrounds, and experiences. Even if you don't meet every requirement, we encourage you to apply. We believe in growth, and we're excited to see what you can bring. At Kyndryl, employee feedback has told us that our number one driver of employee engagement is belonging. That sense of belonging being a valued, respected, trusted member of the team is fundamental to our culture and fueling great experiences for our customers. This dedication to welcoming everyone into our company means that Kyndryl gives you the ability to thrive and contribute to our culture of empathy and shared success. That's The Kyndryl Way.
• What You Can Expect.
• Your career with us isn't just a job it's an adventure with purpose. We offer a dynamic, hybrid-friendly culture that supports your well-being and empowers you to grow. Our Be Well programs are thoughtfully designed to support your financial, mental, physical, and social health because we know that when you feel your best, you do your best.
• From your very first day, you'll dive into impactful work that powers the systems our customers rely on every day. You won't just contribute you'll make a difference, tackling meaningful projects that sharpen your skills and fuel your growth.
• We're here to champion your journey. With powerful tools to chart your career path, personalized development goals aligned with your ambitions, and continuous feedback to keep you inspired and on track, you'll have everything you need to thrive and evolve. You'll develop in-demand skills to grow your career and achieve your ambitions with access to cutting-edge learning opportunities from certifications with Microsoft, Google, and Amazon to coaching and hands-on experiences. And through it all, you'll be part of a culture that values empathy, restless learning, and a devotion to shared success.
• We want you to thrive here and we're committed to helping you do just that. Ready to make an impact? Join us and help shape what's next.
• Get Referred!.
• If you know someone that works at Kyndryl, when asked 'How Did You Hear About Us' during the application process, select 'Employee Referral' and enter your contact's Kyndryl email address.

ทักษะ:

Microsoft Exchange, Cloud Computing, Windows Server, Architecture, Red Hat

ประเภทงาน:

งานประจำ

• Participate in the design of all information technology systems and infrastructure.
• Facilitate and monitor all installed systems and infrastructure.
• Configure and administer a defined technology/system (e.g., Hardware, Operating Systems) in support of on-going operations and projects.
• Analyzes and provide solution on computer applications and system for team, customers and end user; provides a wide range of in-depth technical assistance to user support staff.
• Provides solution to integrated hardware, software, system infrastructure, data back-up and recovery specifications.
• Manage incidents and requests for a defined technology environment.
• Maintains quality service by establishing and enforcing organization standards.
• Perform additional tasks as needed.
• Bachelor's degree or higher in area of Computer Engineering, Computer Science, IT or related fields.
• Minimum of 5 years' experience in IT as System Engineer.
• Must have experience with.
• Operating System (e.g., Windows Server 2003-2012, CentOS, Linux, Redhat, Ubuntu ).
• Enterprise hardware architecture (e.g., Server, Storage).
• Virtualization and containerization (e.g., VMware, Hyper-V).
• Web application service (e.g., Nginx,Apache Tomcat and IIS).
• Microsoft Exchange mail system.
• Active directory user and computer service.
• DNS and DHCP service.
• Group policy on Windows domain controller.
• Power Shell and Batchfile script.
• Monitoring system.
• Backup and recovery software (e.g., Backup Exec, Veeam).
• Public Cloud computing service.
• Proven experience in overseeing the design, development, and implementation of software systems, applications, and related products.
• Proven experience with systems planning, security principles, and general software management best practices.
• 5-day work week 5 วันทำงานต่อสัปดาห์.
• Annual Leave วันหยุดพักผ่อนประจำปี.
• Business Leave วันลากิจ.
• Birthday Leave วันลาพิเศษในเดือนเกิด.
• Family Care Leave วันลาเพื่อดูแลคนในครอบครัวเมื่อเจ็บป่วย.
• Paternity Leave วันลาเพื่อดูแลภรรยาหลังคลอดบุตร.
• Sterilization Leave วันลาเพื่อทำหมัน.
• Maternity Leave วันลาคลอดบุตร.
• Child allowance before kindergarten สนับสนุนค่าใช้จ่ายบุตรพนักงานก่อนวัยอนุบาล.
• Annual flu vaccination วัคซีนป้องกันไข้หวัดใหญ่ประจำปีฟรี.
• Group Life Insurance ประกันชีวิต(กลุ่ม).
• Outpatient medical benefits (OPD) ค่ารักษาพยาบาลผู้ป่วยนอก.
• Inpatient medical benefits (IPD) ค่ารักษาพยาบาลผู้ป่วยใน.
• Accident medical coverage ค่ารักษาพยาบาลกรณีอุบัติเหตุ.
• Dental benefits of THB 3,000 per year ค่าทันตกรรม 3,000 บาทต่อปี.
• Annual health check-up by BDMS ตรวจสุขภาพประจำปีกับโรงพยาบาลชั้นนำเครือ BDMS.
• Provident Fund กองทุนสำรองเลี้ยงชีพ.
• Social Security ประกันสังคม.
• Funeral assistance benefit เงินช่วยเหลือฌาปนกิจ.
• Discounts on affiliated companies' products or services, subject to company announcement ส่วนลดสำหรับสินค้าหรือบริการราคาพิเศษของบริษัทในเครือตามประกาศของบริษัท.

ทักษะ:

Data Warehousing, Risk Management, Data Analysis, TensorFlow, Big Data

ประเภทงาน:

งานประจำ

• Design, develop and deploy advanced machine learning and artificial intelligence models focused on financial risk analytics, credit risk assessment, market risk analysis and fraud detection.
• Lead the end-to-end data science lifecycle, from problem definition and data exploration through model validation, implementation and ongoing performance monitoring.
• Mentor and supervise junior data scientists and analytical staff, fostering a culture of excellence, continuous learning and collaborative problem-solving within the te ...
• Conduct comprehensive exploratory data analysis on large-scale financial datasets to identify patterns, anomalies and opportunities for predictive modelling.
• Develop robust statistical models and econometric frameworks to quantify and forecast financial risks across various asset classes and business segments.
• Create clear and compelling data visualisations and reports that translate complex analytical findings into actionable business recommendations for senior management and risk committees.
• Collaborate closely with risk management, compliance, trading and operations teams to understand business requirements and ensure analytical solutions align with strategic objectives.
• Establish and maintain rigorous model governance frameworks, including validation protocols, backtesting procedures and documentation standards to ensure regulatory compliance.
• Stay abreast of emerging trends, methodologies and technologies in financial AI, machine learning and risk analytics, and evaluate their applicability to our business.
• Optimise data pipelines and analytical infrastructure to enhance processing efficiency, scalability and data quality across analytical systems.
• What we're looking for.
• Master's degree or higher in Data Science, Machine Learning, Statistics, Mathematics, Physics, Computer Science or a related quantitative discipline.
• Minimum 7-10 years of professional experience in data science, machine learning engineering or advanced analytics, with at least 4-5 years specifically focused on financial services, risk analytics or quantitative finance.
• Demonstrated expertise in building and deploying machine learning models in production environments, with proficiency in supervised learning, unsupervised learning, ensemble methods and deep learning techniques.
• Strong proficiency in programming languages such as Python, R or Scala, with experience in relevant libraries and frameworks (e.g. scikit-learn, TensorFlow, PyTorch, XGBoost).
• Solid understanding of financial concepts including credit risk, market risk, operational risk, counterparty risk, regulatory capital requirements and risk measurement methodologies.
• Experience with big data technologies and distributed computing frameworks such as Apache Spark, Hadoop or cloud-based analytics platforms (AWS, GCP, Azure).
• Proven track record of leading analytical projects, mentoring junior staff and driving cross-functional collaboration in a complex organisational environment.
• Strong statistical knowledge including hypothesis testing, causal inference, time series analysis and experimental design.
• Experience with financial data sources, APIs and market data platforms; familiarity with data warehousing and ETL processes is advantageous.
• Excellent communication skills with the ability to present technical concepts clearly to both technical and non-technical audiences.
• Knowledge of financial regulations such as Basel III, IFRS 9, Dodd-Frank or equivalent regional frameworks is highly desirable.
• Certification in machine learning, data science or related disciplines is a plus.

ประสบการณ์:

3 ปีขึ้นไป

ทักษะ:

Product Development, Postgre SQL, Automation, Javascript, Kubernetes

ประเภทงาน:

งานประจำ

• Design, develop, and fine-tune Generative AI solutions using leading LLMs such as GPT-4o, Claude (Anthropic), Gemini, and open-source models (LLaMA, Mistral, etc.).
• Build and maintain End-to-End AI Chatbot systems from prompt engineering and LLM integration to deployment and monitoring.
• Develop production-grade RAG (Retrieval-Augmented Generation) Chatbot pipelines integrating vector search, document chunking, embedding models, and LLM inference.
• Implement and manage Vector Storage solutions using FAISS, Qdrant, Weaviate, Pinecone, or similar technologies for semantic search and knowledge retrieval.
• Design and deploy Agentic AI systems using frameworks such as LangGraph, AutoGen, CrewAI, or custom multi-agent orchestration workflows.
• Integrate AI capabilities with enterprise APIs, databases, and internal platforms via LangChain, LlamaIndex, or equivalent tooling.
• Stay current with rapidly evolving AI/ML tools including Hugging Face, Ollama, vLLM, OpenAI APIs, Vertex AI, AWS Bedrock, and Azure OpenAI Service.
• AI Product Development & MLOps.
• Own the end-to-end AI product lifecycle: requirements gathering, model selection, development, testing, deployment, and continuous improvement.
• Build and manage scalable AI inference pipelines with performance monitoring, logging, and cost optimization.
• Design prompt engineering strategies, evaluation frameworks, and guardrails for safe and reliable LLM outputs.
• Implement CI/CD workflows for AI models using MLflow, DVC, or similar MLOps tools.
• Collaborate with Data Science and Engineering teams to productionize machine learning and AI models.
• Identify opportunities to embed AI capabilities into business workflows, automation, and decision-making processes.
• Data Engineering & Platform (Foundational Awareness).
• Understand the fundamentals of data pipeline concepts (ETL/ELT, batch and streaming) to effectively collaborate with Data Engineering teams.
• Able to read, query, and work with data from common platforms such as Databricks, Snowflake, BigQuery, or PostgreSQL.
• Understand data flow from source systems to data warehouses/lakehouses to inform AI model inputs and outputs.
• Familiar with vector database concepts and embedding pipelines sufficient to configure and use them in AI projects.
• Capable of communicating data requirements clearly to Data Engineers when building AI features or knowledge bases.
• Collaboration & Innovation.
• Partner with product managers, business stakeholders, and engineers to translate business requirements into AI solutions.
• Contribute to and promote best practices for AI development, testing, documentation, and responsible AI usage.
• Mentor junior engineers and share knowledge on emerging AI tools, frameworks, and research.
• Evaluate and adopt new AI/ML technologies and frameworks to keep the team at the forefront of innovation.
• Effectively manage multiple priorities and deliver high-quality solutions independently and as part of a team.
• Bachelor's degree or higher in Computer Science, Computer Engineering, Information Technology, Artificial Intelligence, or a related field.
• 3+ years of hands-on experience in AI/ML engineering with a focus on Generative AI and NLP applications.
• Proven experience building Generative AI solutions using GPT-4o, Claude (Anthropic), Gemini, or equivalent LLMs this is a must.
• Hands-on experience with RAG Chatbot development: embedding pipelines, chunking strategies, retrieval tuning, and LLM response generation.
• Proficiency in Vector Storage technologies such as FAISS, Qdrant, Weaviate, Pinecone, or ChromaDB.
• Experience building End-to-End Chatbot systems including intent handling, context management, multi-turn dialogue, and API integration.
• Practical knowledge of Agentic AI frameworks (LangGraph, AutoGen, CrewAI, or similar) for building multi-step, tool-using AI agents.
• Strong Python programming skills Python (required), SQL, JavaScript/TypeScript (a plus).
• Familiarity with popular AI/ML tools and platforms: LangChain, LlamaIndex, Hugging Face, Ollama, vLLM, OpenAI SDK, Vertex AI, AWS Bedrock, or Azure OpenAI.
• Experience with prompt engineering techniques including few-shot prompting, chain-of-thought, structured output, and function calling.
• Ability to evaluate LLM outputs using metrics and frameworks (RAGAS, TruLens, or custom eval pipelines).
• AI Frameworks: LangChain, LlamaIndex, LangGraph, AutoGen, CrewAI, Hugging Face Transformers.
• LLM Platforms: OpenAI (GPT-4o), Anthropic Claude, Google Gemini, Meta LLaMA, Mistral.
• Vector Databases: FAISS, Qdrant, Weaviate, Pinecone, ChromaDB.
• Cloud & Data: AWS / GCP / Azure AI services, Databricks, Snowflake, PostgreSQL.
• MLOps: MLflow, DVC, Docker, Kubernetes (a plus).
• Big Data: Apache Spark, Kafka (a plus).
• Experience in Retail or E-Commerce AI applications (e.g., recommendation engines, pricing AI, conversational commerce).
• Familiarity with fine-tuning and PEFT techniques (LoRA, QLoRA) for LLMs.
• Knowledge in machine/statistical learning, computer vision, or time series forecasting.
• Experience with AI safety, hallucination mitigation, and responsible AI practices.
• Contributions to open-source AI projects or published AI research.

ประสบการณ์:

5 ปีขึ้นไป

ทักษะ:

Architecture, Leadership Skill, Python

ประเภทงาน:

งานประจำ

• Location of CP AXTRA (Head Office) 3-4 Days: https://share.google/V5Q7MuC44FS341Xhx.
• Location of CP AXTRA Lotus's (Nawamin Office) 1 day: https://maps.app.goo.gl/6cHYiNFfwE8EqrFU6.
• Working style.
• 4-5 Days at the office + work from anywhere.
• Accompany senior management on store visits on Saturdays (half-day or full-day, not every week.
• AI & Advanced Analytics Enablement.
• Lead the design, development, and deployment of enterprise AI, Machine Learning, and Generative AI solutions to support business transformation (e.g., pricing, promotion, automation, recommendation, demand forecasting, customer insights, and intelligent decision support).
• Build and manage scalable data pipelines supporting AI/ML model training, inference, feature engineering, Feature Store, RAG knowledge bases, and LLM applications.
• Develop reusable datasets, AI-ready data products, feature engineering pipelines, and semantic data models for AI Engineers, Data Scientists, and Business Analytics teams.
• Partner closely with AI Engineers to design, deploy, productionize, and scale AI/ML models, LLM applications, Agentic AI, AI Chatbots, Recommendation Systems, and Mobile AI applications.
• Design and maintain data ingestion pipelines for structured, semi-structured, and unstructured data from enterprise systems, APIs, databases, files, event streams, IoT devices, and third-party platforms.
• Develop scalable data pipelines supporting document ingestion, embedding generation, metadata management, vector indexing, and retrieval workflows for RAG applications.
• Identify opportunities to embed AI into business workflows and operational decision-making to improve efficiency, customer experience, and business value.
• Data Platform & Engineering Leadership.
• Own end-to-end enterprise data architecture from source systems to Data Lake, Lakehouse, Data Warehouse, Feature Store, Semantic Layer, and AI-serving layers.
• Design, develop, and optimize scalable ETL/ELT pipelines supporting batch, micro-batch, streaming, and near real-time data processing.
• Design and maintain workflow orchestration for enterprise data pipelines using Databricks Workflows, Apache Airflow, or equivalent orchestration frameworks.
• Develop enterprise-scale Big Data solutions using Apache Spark and distributed computing frameworks.
• Design scalable logical and physical data models while optimizing database architecture for performance, scalability, reliability, and cost efficiency.
• Ensure enterprise data quality, governance, lineage, metadata management, observability, security, and compliance across data platforms.
• Implement automated data validation, monitoring, logging, alerting, and observability to ensure production-grade data reliability.
• Optimize SQL queries, Spark workloads, partitioning strategies, storage formats, and compute resources for maximum performance and cost efficiency.
• Analyze complex technical issues, identify root causes, troubleshoot production problems, and recommend infrastructure and platform improvements.
• Select, evaluate, and integrate modern data engineering tools, cloud technologies, and AI platform frameworks to support evolving business needs.
• Continuously evaluate emerging technologies in Big Data, Lakehouse Architecture, Data Platform Engineering, Cloud Computing, and AI Platform Engineering.
• AI Platform & Infrastructure.
• Build and maintain enterprise AI data infrastructure supporting LLM, RAG, Agentic AI, AI Chatbots, Recommendation Engines, Intelligent Search, and Intelligent Automation platforms.
• Design and implement scalable AI data pipelines supporting batch, streaming, vector search, embedding pipelines, and Retrieval-Augmented Generation (RAG) architectures.
• Design scalable APIs, data services, and integration layers connecting AI applications with enterprise systems and digital platforms.
• Collaborate with AI Engineers to prepare high-quality datasets for LLM fine-tuning, prompt engineering, model evaluation, inference, and continuous model improvement.
• Support deployment and operationalization of AI products using DataOps, MLOps, CI/CD, containerization, and modern software engineering practices.
• Drive continuous improvements in platform scalability, availability, security, observability, resilience, and operational efficiency.
• Team Leadership & Capability Building.
• Lead, mentor, and develop a high-performing team of Data Engineers, AI Engineers, and Analytics professionals.
• Foster engineering excellence through best practices in architecture design, coding standards, testing, code reviews, deployment, technical documentation, and software engineering.
• Drive architecture reviews, technical design reviews, engineering governance, and platform standardization across the engineering organization.
• Define engineering standards, technical roadmaps, platform architecture, and technology strategy aligned with business objectives.
• Collaborate closely with Product Owners, Business Stakeholders, AI Engineers, Data Scientists, Solution Architects, Infrastructure, and DevOps teams.
• Provide hands-on technical leadership with a strong engineering mindset and willingness to troubleshoot complex production systems.
• Promote continuous learning, knowledge sharing, innovation, and adoption of emerging technologies across the engineering team.
• Bachelor's degree or higher in Computer Science, Computer Engineering, Information Technology, Artificial Intelligence, Data Engineering, Management Information Systems, or a related field.
• 6+ years.
• of experience in.
• Data Platform Engineering, Data Engineering, Big Data, or AI Platform development,.
• with experience leading engineering teams.
• Strong experience designing and implementing enterprise-scale Data Lake, Lakehouse, Data Warehouse, or Modern Data Platform architectures.
• Expert proficiency in SQL, Databricks SQL, PostgreSQL, database design, and query performance optimization.
• Strong programming skills in Python.
• Hands-on experience with Apache Spark, Databricks, Delta Lake, Spark SQL, Unity Catalog, and distributed data processing.
• Strong experience designing and developing scalable ETL/ELT pipelines and workflow orchestration.
• Experience with streaming technologies such as Spark Structured Streaming, Kafka, or equivalent.
• Experience building enterprise-scale data platforms supporting AI/ML, Advanced Analytics, and Generative AI applications.
• Experience with LLM, RAG, AI Chatbots, Agentic AI, Vector Databases, Embedding Pipelines, Feature Store, or Recommendation Systems is highly preferred.
• Experience integrating enterprise applications through REST APIs, event-driven architectures, and microservices.
• Strong understanding of Data Governance, Data Quality, Data Lineage, Metadata Management, Data Security, and Data Observability.
• Experience with Azure, AWS, or Google Cloud Platform is preferred.
• Experience with Git, Docker, Kubernetes, CI/CD, DataOps, MLOps, MLflow, or Infrastructure as Code is an advantage.
• Retail, Wholesale, or E-Commerce industry experience is highly preferred.
• Proven track record in delivering enterprise AI platforms, data platforms, or large-scale analytics solutions.
• Strong analytical thinking, problem-solving, communication, stakeholder management, and leadership skills.
• Passion for building scalable engineering platforms, mentoring teams, and delivering business impact through data and AI.
• CP AXTRA | Lotus's.
• CP AXTRA Public Company Limited.
• Nawamin Office: Buengkum, Bangkok 10230, Thailand.
• By applying for this position, you consent to the collection, use and disclosure of your personal data to us, our recruitment firms and all relevant third parties for the purpose of processing your application for this job position (or any other suitable positions within Lotus's and its subsidiaries, if any). You understand and acknowledge that your personal data will be processed in accordance with the law and our policy.".

ประสบการณ์:

6 ปีขึ้นไป

ทักษะ:

Cloud Computing, Architecture, Postgre SQL, Automation, Leadership Skill

ประเภทงาน:

งานประจำ

• AI & Advanced Analytics Enablement.
• Lead the design, development, and deployment of enterprise AI, Machine Learning, and Generative AI solutions to support business transformation (e.g., pricing, promotion, automation, recommendation, demand forecasting, customer insights, and intelligent decision support).
• Build and manage scalable data pipelines supporting AI/ML model training, inference, feature engineering, Feature Store, RAG knowledge bases, and LLM applications.
• Develop reusable datasets, AI-ready data products, feature engineering pipelines, and semantic data models for AI Engineers, Data Scientists, and Business Analytics teams.
• Partner closely with AI Engineers to design, deploy, productionize, and scale AI/ML models, LLM applications, Agentic AI, AI Chatbots, Recommendation Systems, and Mobile AI applications.
• Design and maintain data ingestion pipelines for structured, semi-structured, and unstructured data from enterprise systems, APIs, databases, files, event streams, IoT devices, and third-party platforms.
• Develop scalable data pipelines supporting document ingestion, embedding generation, metadata management, vector indexing, and retrieval workflows for RAG applications.
• Identify opportunities to embed AI into business workflows and operational decision-making to improve efficiency, customer experience, and business value.
• Data Platform & Engineering Leadership.
• Own end-to-end enterprise data architecture from source systems to Data Lake, Lakehouse, Data Warehouse, Feature Store, Semantic Layer, and AI-serving layers.
• Design, develop, and optimize scalable ETL/ELT pipelines supporting batch, micro-batch, streaming, and near real-time data processing.
• Design and maintain workflow orchestration for enterprise data pipelines using Databricks Workflows, Apache Airflow, or equivalent orchestration frameworks.
• Develop enterprise-scale Big Data solutions using Apache Spark and distributed computing frameworks.
• Design scalable logical and physical data models while optimizing database architecture for performance, scalability, reliability, and cost efficiency.
• Ensure enterprise data quality, governance, lineage, metadata management, observability, security, and compliance across data platforms.
• Implement automated data validation, monitoring, logging, alerting, and observability to ensure production-grade data reliability.
• Optimize SQL queries, Spark workloads, partitioning strategies, storage formats, and compute resources for maximum performance and cost efficiency.
• Analyze complex technical issues, identify root causes, troubleshoot production problems, and recommend infrastructure and platform improvements.
• Select, evaluate, and integrate modern data engineering tools, cloud technologies, and AI platform frameworks to support evolving business needs.
• Continuously evaluate emerging technologies in Big Data, Lakehouse Architecture, Data Platform Engineering, Cloud Computing, and AI Platform Engineering.
• AI Platform & Infrastructure.
• Build and maintain enterprise AI data infrastructure supporting LLM, RAG, Agentic AI, AI Chatbots, Recommendation Engines, Intelligent Search, and Intelligent Automation platforms.
• Design and implement scalable AI data pipelines supporting batch, streaming, vector search, embedding pipelines, and Retrieval-Augmented Generation (RAG) architectures.
• Design scalable APIs, data services, and integration layers connecting AI applications with enterprise systems and digital platforms.
• Collaborate with AI Engineers to prepare high-quality datasets for LLM fine-tuning, prompt engineering, model evaluation, inference, and continuous model improvement.
• Support deployment and operationalization of AI products using DataOps, MLOps, CI/CD, containerization, and modern software engineering practices.
• Drive continuous improvements in platform scalability, availability, security, observability, resilience, and operational efficiency.
• Team Leadership & Capability Building.
• Lead, mentor, and develop a high-performing team of Data Engineers, AI Engineers, and Analytics professionals.
• Foster engineering excellence through best practices in architecture design, coding standards, testing, code reviews, deployment, technical documentation, and software engineering.
• Drive architecture reviews, technical design reviews, engineering governance, and platform standardization across the engineering organization.
• Define engineering standards, technical roadmaps, platform architecture, and technology strategy aligned with business objectives.
• Collaborate closely with Product Owners, Business Stakeholders, AI Engineers, Data Scientists, Solution Architects, Infrastructure, and DevOps teams.
• Provide hands-on technical leadership with a strong engineering mindset and willingness to troubleshoot complex production systems.
• Promote continuous learning, knowledge sharing, innovation, and adoption of emerging technologies across the engineering team.
• Bachelor's degree or higher in Computer Science, Computer Engineering, Information Technology, Artificial Intelligence, Data Engineering, Management Information Systems, or a related field.
• 6+ years of experience in Data Platform Engineering, Data Engineering, Big Data, or AI Platform development, with experience leading engineering teams.
• Strong experience designing and implementing enterprise-scale Data Lake, Lakehouse, Data Warehouse, or Modern Data Platform architectures.
• Expert proficiency in SQL, Databricks SQL, PostgreSQL, database design, and query performance optimization.
• Strong programming skills in Python.
• Hands-on experience with Apache Spark, Databricks, Delta Lake, Spark SQL, Unity Catalog, and distributed data processing.
• Strong experience designing and developing scalable ETL/ELT pipelines and workflow orchestration.
• Experience with streaming technologies such as Spark Structured Streaming, Kafka, or equivalent.
• Experience building enterprise-scale data platforms supporting AI/ML, Advanced Analytics, and Generative AI applications.