เงื่อนไขการค้นหา

ทักษะ:

ETL, SQL

ประเภทงาน:

งานประจำ

• Are you a technically minded data professional who enjoys solving complex data challenges and making sure information flows accurately across systems and teams? As Data Integration Specialist - ETL & Data Loading at Allianz Partners in Bangkok, you will be responsible for the end-to-end process of loading beneficiary data into our portfolio management system - ensuring alignment with business objectives and the needs of our partners, claims teams, and reporting functions. Allianz Partners operates as a B2B2C business, connecting corporate partners such as travel companies, automoti ...
• Data Loading & Partner Onboarding.
• Manage the onboarding of business partners at a global level, ensuring smooth integration of beneficiary data into our systems.
• Coordinate with business partners and internal stakeholders on datasets, upload frequency, and data requirements.
• Set up and maintain SFTP connections with business partners, ensuring secure and reliable data transfer.
• Troubleshooting & Issue Resolution.
• Investigate and resolve data loading issues, conducting root cause analysis for recurring problems and implementing preventive measures.
• Manage multiple requests and prioritise effectively to ensure timely resolution.
• Communicate outcomes and recommendations clearly to relevant stakeholders.
• Process Optimisation & Compliance.
• Identify and implement improvements to data loading processes to enhance efficiency, accuracy, and scalability.
• Maintain awareness of data privacy regulations including PDPA and GDPR, ensuring day-to-day data handling practices are aligned with company policies.
• Maintain a clear understanding of data touchpoints across all Lines of Business.
• Stakeholder Collaboration.
• Work closely with operations, contract implementation, claims, underwriting, and digital teams to ensure seamless data integration.
• Act as a reliable point of contact for business partners and internal teams, bridging technical and business requirements.
• Quality Assurance & Testing.
• Support and participate in User Acceptance Testing (UAT) to ensure data quality, system functionality, and alignment with business requirements.
• Implement monitoring and logging mechanisms to ensure transparency and traceability of data activities.
• Continuous Improvement.
• Stay current with trends, tools, and best practices in data loading and management.
• Contribute ideas and improvements to enhance team processes and overall data operations.
• Support knowledge sharing within the team to build collective capability.
• What You'll Bring.
• Solid experience in data loading, data integration, or a related data management role.
• Hands-on experience with ETL tools such as Pentaho Data Integration (Kettle), SSIS, or similar platforms.
• Proficiency in SQL for data querying, validation, and manipulation.
• Experience setting up and managing SFTP connections or similar secure file transfer protocols.
• Familiarity with scripting languages such as Python or JavaScript for data automation is a plus.
• Advanced Excel skills; experience with Power Query or similar reporting tools is an advantage.
• Familiarity with Agile project management tools such as Jira or Confluence is a plus.
• Basic awareness of data privacy regulations - PDPA and/or GDPR - and how they apply to data handling practices.
• Familiarity with AI-powered data tools or automated data quality solutions is an advantage.
• Strong troubleshooting and analytical skills with the ability to resolve data issues independently.
• Good stakeholder management skills - comfortable working with both technical and non-technical teams.
• Customer-centric mindset with a focus on delivering accurate, timely data solutions.
• Strong organisational skills with the ability to manage multiple priorities effectively.
• Strong English proficiency - both written and verbal - is required for this role.
• Must have full rights to work in Thailand - visa sponsorship is not provided.
• What We Offer.
• Competitive salary and performance-based bonus.
• Provident fund contributions.
• Comprehensive health insurance coverage.
• Flexible working arrangements.
• Annual leave and public holidays in line with Thai employment standards.
• Learning and development opportunities to grow your technical career within Allianz Partners' global network.
• Exposure to international data operations and cross-functional technology projects.
• A collaborative, inclusive work environment at Soi Petchaburi 35, Ratchatewi, Bangkok.
• f you're excited but don't meet every single requirement, apply anyway - we value potential and learning agility. Only shortlisted candidates will be contacted.
• 98328 | Data & AI | Professional | Allianz Partners | Full-Time | Permanent.
• Allianz Partners is a world leader in B2B2C insurance and assistance, offering global solutions across automotive, travel, health, and home assistance. Present in over 75 countries, we combine the strength of the Allianz Group with a local, innovation-driven mindset. In Thailand, our technology and data teams are part of a growing hub supporting digital transformation across the APAC region and beyond. At Allianz Partners, we are committed to building an inclusive workplace where every team member can grow, contribute, and thrive.
• Allianz Group is one of the most trusted insurance and asset management companies in the world. Caring for our employees, their ambitions, dreams and challenges is what makes us a unique employer. We are united by a shared commitment: to put our customers first and at the centre of everything we do. Their needs inspire our thinking and guide our actions. Together, we can build an environment where everyone feels empowered and confident to explore, grow and shape a better future - for our customers and for the world around us. At Allianz, we stand for unity: we believe that a united world is a more prosperous world, and we are dedicated to consistently advocating for equal opportunities for all. The foundation for this is our inclusive workplace, where people and performance both matter, and where integrity, fairness, inclusion and trust are at the heart of our culture. We therefore welcome applications regardless of ethnicity or cultural background, age, gender, nationality, religion, social class, disability or sexual orientation, or any other characteristics protected under applicable local laws and regulations. Join us. Let's care for tomorrow.
• To Recruitment Agencies.
• We have an in-house recruitment team that focuses on sourcing great candidates directly. Therefore, we do not accept unsolicited resumes from agencies or search firm recruiters. When we do work with recruitment agencies, that engagement is formalized by a contract. Fees will only be paid when such a contract is in place. Without a contract, we will not accept invoices related to unsolicited resumes, even if the candidate is ultimately hired. Please do not contact hiring managers directly.

ทักษะ:

Problem Solving, PowerShell, ETL, SQL

ประเภทงาน:

งานประจำ

• Provide technical leadership for manufacturing data operations, ETL services, data-flow reliability, monitoring, recovery, and continuous improvement.
• Define technical standards, operational procedures, service ownership boundaries, escalation paths, and readiness requirements for critical data services.
• Guide the design and improvement of Apache NiFi pipelines, data collection, validation, transformation, routing, replay, reconciliation, exception handling, and lineage.
• Lead complex incident investigation, technical recovery, root-cause analysis, corrective action, and prevention of recurring failures.
• Review operational trends and risks to prioritize monitoring improvements, automation, resiliency, documentation, and technical debt reduction.
• Coordinate technical work across application, infrastructure, network, cybersecurity, database, enterprise data, and factory teams.
• Enable the 24/7 L1 FIS Operations team with current knowledge-base articles, runbooks, standard procedures, troubleshooting guides, recovery instructions, and clear escalation criteria.
• Plan and deliver technical training, knowledge-transfer sessions, practical troubleshooting exercises, and coaching for L1 personnel.
• Define the standard incidents L1 can resolve, first-response checks to perform, evidence to collect, and conditions for escalation.
• Act as the L2/L3 escalation point for incidents that cannot be resolved through approved L1 procedures.
• Analyze logs, pipeline status, interfaces, files, messages, SQL results, dependencies, and service behavior to isolate complex failures.
• Recover and reconcile disrupted data flows, validate downstream delivery, support business-impact communication, and restore services safely.
• Lead deep technical investigation of recurring, high-impact, or cross-system issues and implement permanent fixes, monitoring controls, failover improvements, automation, and data-quality safeguards.
• Convert L2/L3 findings into improved L1 knowledge, diagnostics, alerts, training, and preventive controls.
• Support manufacturing data services across Slider, HGA, HSA, Drive, SDET, ComET, DVL, FDB, ETS, and related environments.
• Monitor data arrival, pipeline execution, queues, service health, failures, recovery, and downstream delivery.
• Support factory data transfers including Slider-to-HGA, HGA-to-HSA/Drive, and HGA-to-EDW flows.
• Use strong SQL and database knowledge to troubleshoot data issues, validate schemas and interfaces, and identify database-related dependencies.
• Work closely with Oracle and PostgreSQL database teams on connectivity, access, performance, capacity, backup/recovery, patching, high availability, security, migration, and upgrade activities.
• Support FISGetPutServer and FISFactoryService installation, configuration, monitoring, troubleshooting, failover, relay, and feed-forward integration.
• Provide advanced support for SeaTrack, Unify SeaTrack, PARIS, CMS, FDB/DVL, work-order tools, equipment tracking, and shop-floor event-history integrations.
• Maintain technical designs, service inventories, configuration records, data-flow maps, runbooks, recovery procedures, support contacts, and escalation matrices.
• You are a hands-on senior IT professional who can lead technical data-operations practices without being a people manager. You translate deep technical knowledge into clear guidance for frontline operations, take ownership of difficult escalations, coach L1 personnel, investigate cross-system data issues, and coordinate specialist teams until services are stabilized and preventive improvements are implemented.
• Bachelor's degree in Computer Science, Information Technology, Computer Engineering, Data Engineering, or a related field, or equivalent practical experience.
• Strong experience in production data operations, ETL/data integration, data-flow services, or manufacturing IT.
• Experience providing L2/L3 production support within a tiered 24/7 support and escalation model.
• Ability to lead technical problem solving and develop knowledge-base articles, runbooks, troubleshooting guides, and L1 training material.
• Experience building or operating ETL/data-flow pipelines; Apache NiFi experience is strongly preferred.
• Strong SQL and relational-database knowledge, including Oracle and PostgreSQL concepts, connectivity, schemas, transactions, query troubleshooting, performance considerations, and data integrity.
• Ability to work effectively with DBA teams on database incidents, access, backup/recovery, high availability, capacity, patching, migration, and performance issues.
• Strong incident leadership, root-cause analysis, technical communication, coaching, and cross-team collaboration skills.
• Preferred: Experience supporting high-volume manufacturing, MES/FIS, shop-floor, equipment integration, or traceability systems.
• Preferred: Participation in Oracle-to-PostgreSQL migration or application stabilization in partnership with DBA teams.
• Preferred: Python, PowerShell, Bash, or equivalent scripting for operational automation and data validation.
• Preferred: Kafka or event streaming, enterprise data warehouses, observability platforms, or data-quality frameworks.
• Preferred: Knowledge of ITIL, incident/problem management, change management, BC/DR, cybersecurity, and audit controls.
• Teparuk Thailand.
• Home to over 4,000 employees, our Teparuk site specializes in producing nano-recording heads - a crucial component for the read/write functionality of hard disk drives. At our Teparuk facility, work is both productive and enjoyable. You and your colleagues can grab breakfast, lunch, dinner, and snacks at our 24/7 on-site canteen and coffee shop. Stay active by taking a few laps around our running track or participating in volleyball, basketball, table tennis, badminton, or football at our on-site gymnasium and fitness center. We also offer a variety of activities, including music, dance, and aerobic classes. Alternatively, unwind in our lush green areas. Consider joining any of our employee resource groups (ERGs), such as Seagate Women in Leadership Network (SWLN), Seagate PRIDE: Thailand chapter, or Seagate's parents and caregivers' group. These ERGs provide educational and fun activities. Additionally, enjoy on-site festivals, celebrations, and opportunities to give back to the local community.
• Information at a Glance.
• About Us.
• With more than four decades of storage innovation, Seagate empowers humanity to thrive in the data age and helps people and businesses navigate the ever-expanding data landscape.
• We craft precision-engineered, cutting-edge solutions that help the world store and manage exponential data growth.
• Seagate is powered by our talented and passionate workforce of 29,000 employees across the globe who embody our core values: integrity, innovation, and inclusion. Striving towards excellence every single day, we show up with these values for our customers, business partners, shareholders, and communities alike.
• Join us and get inspired to make a difference in the datasphere!.
• Seagate is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, race, color, ancestry, national origin, citizenship status, physical or mental disability, genetic information, marital status, sex (which includes pregnancy, childbirth, breastfeeding, or related medical conditions), gender, gender identity, gender expression, sexual orientation, religion, military and veteran status, or other status protected by applicable law. We will consider for employment qualified applicants with arrest and conviction records. EEO Know Your Rights Poster.
• Seagate will provide reasonable accommodation with the application process upon request as required to comply with applicable laws. If you need assistance or accommodation due to a disability, you may contact us at [email protected].
• All Seagate jobs will remain open for a minimum of seven days.
• For information on how Seagate collects and uses your personal information during the application process, please review the Applicant Privacy Statement.

ทักษะ:

Architecture, Automation, Big Data, Python, Docker

ประเภทงาน:

งานประจำ

• Data Pipeline & Architecture.
• ออกแบบและสร้างท่อส่งข้อมูล (ETL/ELT Pipelines) ทั้งแบบ Batch และ Real-time.
• เชื่อมต่อข้อมูลจากแหล่งต่าง ๆ เช่น Database, REST APIs, และ Message Queues.
• ออกแบบและวางรากฐานโครงสร้างข้อมูล (Data Schema) เพื่อรองรับการทำ Data Analytics เชิงลึก พร้อมทั้งวางแผนและบริหารจัดการการพัฒนาเครื่องมือภายใน (Internal Tools).
• ตรวจสอบและแก้ไขปัญหา Query ที่ทำงานช้า (Slow Query).
• ออกแบบ Index และโครงสร้างข้อมูลเพื่อเพิ่มประสิทธิภาพการดึงข้อมูล.
• Data Quality & Monitoring.
• ตรวจสอบความถูกต้อง (Data Validation) และความสะอาดของข้อมูลก่อนนำเข้าสู่ระบบ.
• สร้างระบบ Monitoring และ Alerting เมื่อระบบ Pipeline เกิดข้อผิดพลาด รวมถึงพบความผิดปกติของ Data.
• DataOps & Automation.
• ใช้ GitLab CI/CD ในการทำ Automated Testing และ Deploy ระบบ Pipeline.
• จัดการ Containerization ด้วย Docker เพื่อให้ระบบทำงานได้เสถียรในทุก Environment.
• Collaboration & Documentation.
• ทำงานร่วมกับ Data Analyst และทีม Developer เพื่อเปลี่ยนความต้องการทางธุรกิจให้เป็น Technical Solution.
• จัดทำเอกสาร Data Dictionary และ Data Lineage เพื่อความโปร่งใสของที่มาข้อมูล.
• ทักษะทางเทคนิค (Technical Skills).
• Languages: Advanced SQL (Window Functions, CTEs), และ Python (Pandas, PySpark).
• Concepts: เข้าใจหลักการ Data Warehouse, Data Lake, และ Big Data สถาปัตยกรรมต่าง ๆ.
• Cloud: มีประสบการณ์ใช้งาน Cloud Data Warehouse และ Cloud Storage (AWS, Azure, หรือ GCP).
• Version Control: ใช้งาน Git (GitLab, GitHub) ได้คล่องแคล่ว (Branching, Merge Request).
• Data Structures & Algorithms: เข้าใจพื้นฐานในระดับที่สามารถออกแบบโค้ดที่มีประสิทธิภาพ.
• ทักษะเพิ่มเติม (จะพิจารณาเป็นพิเศษ).
• Streaming: มีความเข้าใจระบบ Message Broker เช่น Kafka หรือ RabbitMQ.
• Orchestration: เคยใช้งานเครื่องมือจัดการลำดับงาน เช่น Airflow หรือ Prefect.
• Tools: มีประสบการณ์การใช้ dbt (Data Build Tool) ในการจัดการ SQL Models.
• ผู้ถือสัญชาติไทยเท่านั้น.
• วุฒิการศึกษาระดับปริญญาตรีในสาขา Computer Engineering, IT หรือสาขาที่เกี่ยวข้อง.
• ประสบการณ์ 1-3 ปี (หากเป็นเด็กจบใหม่ ต้องมี Portfolio หรือโปรเจกต์ที่เกี่ยวข้องอย่างชัดเจน).
• มีทักษะการคิดเชิงตรรกะ (Logical Thinking) และความสามารถในการสื่อสารเรื่องเทคนิคให้คนทั่วไปเข้าใจได้ง่าย.
• มีทักษะด้านการสื่อสารและการประสานงานที่มีประสิทธิภาพ.
• มี Growth Mindset.
• สมัครงาน.
• หรือแนะนำผู้อื่น.
• แชร์.
• Facebook.
• Line.
• LinkedIn.
• X (Formerly Twitter).
• Whatsapp.
• Email.

ประสบการณ์:

8 ปีขึ้นไป

ทักษะ:

Architecture, Python, Cloud Computing, ETL, SQL

ประเภทงาน:

งานประจำ

• Data Architecture, Data Engineer & Data Modeling.
• SQL, Python, Spark.
• Data Warehouse, Data Lake, Lakehouse.
• ETL/ELT, Data Orchestration.
• Cloud platforms (Azure / Huawei / AWS).
• Data Governance, Security, and Regulatory Compliance.
• Bachelor's or Master's degree in Computer Science, Engineering, or related fields.
• 8+ years experience in Data Engineering / Data Architecture.
• Strong experience in Insurance domain (Life, Non-Life, or Health) is a big plus.
• Proven experience designing large-scale, enterprise data platforms.
• Hands-on background with modern data technologies and cloud environments.
• Strong communication skills with both technical and business stakeholders.
• The Data Architect is responsible for defining and governing enterprise data architecture to support insurance business operations and analytics. This role ensures scalable, secure, and high-quality data platforms by bridging business requirements and technical data solutions, leveraging strong Data Engineering expertise and deep insurance domain knowledge.
• Key Responsibility.
• Design and own enterprise-level Data Architecture aligned with insurance business strategy.
• Define and maintain architecture for Data Warehouse, Data Lake/Lakehouse, and analytics platforms.
• Translate insurance business requirements (Policy, Claim, Underwriting, Customer) into scalable data solutions.
• Lead data modeling (conceptual, logical, physical) and integration standards.
• Architect and review ETL/ELT pipelines (batch and real-time).
• Establish data governance, data quality, security, lineage, and compliance standards.
• Provide architectural guidance and design reviews for Data Engineering teams.
• Support BI, regulatory reporting, and advanced analytics / AI use cases.
• Job Expectation.
• Define and own end-to-end data architecture for insurance data platforms.
• Deliver scalable and reliable data models for Insurance business.
• Ensure data solutions meet standards for governance, security, quality, and regulatory compliance.
• Provide architectural and design reviews for Data Engineering teams.
• Enable timely delivery of BI, reporting, and advanced analytics use cases.
• Align data architecture decisions with business strategy and technology roadmap.
• Act as a subject matter expert for data-related initiatives within the insurance domain.

ทักษะ:

Cloud Computing, Amazon AWS

ประเภทงาน:

งานประจำ

Designing and implementing data pipelines that extract data from various sources, transform it into a suitable format, and load it into data storage systems. - Integrating data from multiple sources, which can include databases, APIs, logs, and external data sets, to create a unified view of data. - Setting up and managing data warehouses or data lakes where large voulumes of data can be stored and easily accessed for analytical purposes. - Implementing data governance practices to ensure data is managed in a consistent and standardized way across the organization. - Implementing d ...

ทักษะ:

Architecture, Big Data, Teamwork, SQL, ETL

ประเภทงาน:

งานประจำ

• Data management developer is responsible for the successful delivery of business intelligence information to the entire organization and is experienced in BI development and implementations.
• Design stable, reliable and effective data architecture and data mart.
• Understand of BI best practices and be able to create relational structures, dimensional data modeling, structured query language (SQL) skill, data warehouse and reporting techniques, performing ETLs and validating results with business representatives ...
• Support implemented BI solutions by: monitoring and tuning queries and data loads, addressing user questions concerning data integrity, monitoring performance and communicating functional and technical issues.
• Bachelor or Master Degree in Computer Engineering, Computer Science, Technology information systems, or any other IT related field.
• E xperiences in data warehousing development and architecture hands-on physical/logical database and data mart design, experience in big data is advantage.
• Strong SQL development skills -- knowledge of writing complex queries, and query tuning.
• Experience data processing with ETL/BI tools.
• Good communication, collaboration skills and teamwork.

ประสบการณ์:

3 ปีขึ้นไป

ทักษะ:

Architecture, Big Data, Teamwork, SQL, ETL

ประเภทงาน:

งานประจำ

• Data management developer is responsible for the successful delivery of business intelligence information to the entire organization and is experienced in BI development and implementations.
• Design stable, reliable and effective data architecture and data mart.
• Understanding of BI best practices and be able to create relational structures, dimensional data modeling, structured query language (SQL) skill, data warehouse and reporting techniques, performing ETLs and validating results with business representati ...
• monitoring and tuning queries and data loads, addressing user questions concerning data integrity, monitoring performance and communicating functional and technical issues.
• Bachelor or Master Degree in Computer.
• Engineering, Computer Science, Technology information systems, or any other IT related field.
• At least 3 years of experiences in data warehousing development and architecture hands-on physical/logical database and data mart design, experience in big data is advantage.
• Strong SQL development skills -- knowledge of writing complex queries, and query tuning.
• Experience data processing with ETL/BI tools.
• Good communication, collaboration skills and teamwork.

ประสบการณ์:

5 ปีขึ้นไป

ทักษะ:

Architecture, Automation, Leadership Skill, Tableau, Amazon AWS

ประเภทงาน:

งานประจำ

• Own and manage the data warehouse (AWS Redshift), including schema design, performance tuning, query optimization, and cost management.
• Build, maintain, and monitor ETL/ELT pipelines using Airbyte, Segment, and Segment Reverse ETL and similar tools.
• Evaluate and introduce dbt (or equivalent) to bring structure, version control, and testing to data transformations.
• Integrate data sources across the organization: product databases, marketing platforms, sales tools, finance systems, and third-party services.
• Ensure data quality, reliability, and freshness across all pipelines. Build alerting and validation to catch issues before they reach stakeholders.
• Business Intelligence & Reporting.
• Own and manage Metabase as the primary BI platform. Build and maintain core dashboards, data models, and metrics definitions.
• Drive adoption of Metabase as the standard reporting tool across the organization, reducing reliance on ad-hoc spreadsheet-based reporting.
• Build automated reports that replace manual, recurring reporting workflows across departments.
• Define and maintain core business metrics to ensure consistency across all reports and teams.
• Support teams across Product, Marketing, Sales, and Finance in working from shared, trustworthy data, and assist with complex reporting needs.
• Enablement & Coaching.
• Coach and support team members across Product, Marketing, Sales, and Finance in building their own reports and analyses. The objective is to enable self-service, not to become the sole report builder.
• Help non-technical team members understand how to use Metabase, interpret data models, and formulate the right questions.
• Assist with complex reporting needs that go beyond what team members can build independently.
• Improve data literacy across the organization by establishing documentation, training sessions, and accessible data models.
• Marketing Data Engineering.
• Connect marketing performance tools (Supermetrics or equivalent) with the data warehouse to enable unified marketing analytics.
• Build pipelines that consolidate data from paid acquisition channels, attribution tools, and campaign platforms into a single source of truth.
• Support the marketing team in measuring campaign performance, attribution, and ROI through reliable, automated data flows.
• Platform Cost & Optimization.
• Monitor and optimize the cost of the data platform, with a focus on Redshift compute and storage efficiency.
• Evaluate and recommend architectural changes (reserved instances, workload management, data lifecycle policies) to keep costs under control as data volumes grow.
• Track platform costs and report to leadership on trends and optimization opportunities.
• Data Roadmap & Strategy.
• Own the data roadmap for internal tooling, spanning Metabase, Retool data integrations, and marketing data infrastructure.
• Work closely with Product Analysts, Marketing Analysts, Sales Analysts, and Finance Analysts to understand their needs and prioritize data initiatives accordingly.
• Evaluate new tools and technologies as the data function matures, and make recommendations grounded in the organization's actual needs and scale.
• 5+ years of experience in data engineering, analytics engineering, or a combined data role at a technology company.
• Strong proficiency in SQL. You will write complex queries, optimize slow reports, and design data models daily.
• Hands-on experience managing a data warehouse in production, preferably AWS Redshift. You should be comfortable with schema design, query performance tuning, WLM configuration, and cost optimization.
• Experience building and maintaining ETL/ELT pipelines. Hands-on experience with Airbyte, Segment, or similar ingestion tools is strongly preferred.
• Proficiency in Python for data pipeline development, scripting, and automation.
• Experience with BI tools (Metabase, Looker, Tableau, or equivalent). You will own the BI platform and build core dashboards, not just consume them.
• Demonstrated ability to coach and enable non-technical stakeholders to use data tools and build their own reports. This is a core part of the role, not a secondary responsibility.
• Experience integrating data from multiple business systems (CRM, marketing platforms, payment systems, product databases) into a unified data model.
• Strong communication skills in English, both written and verbal. You will work directly with stakeholders across every department.
• Nice to Have.
• Experience with dbt for data transformation, testing, and documentation.
• Experience with Segment Reverse ETL or similar activation tools.
• Familiarity with marketing data engineering (Supermetrics, attribution platforms, ad platform APIs).
• Experience managing AWS Redshift costs and optimizing cluster configurations.
• Background in B2B SaaS or platform companies.
• Experience building a data function from the ground up as the first data hire.
• Familiarity with Retool or similar internal tooling platforms for data-driven applications.
• Working with Manatal.
• This role is based at our Bangkok office in the heart of the city center.
• As a team of diverse cultures and nationalities, English language proficiency is required.
• We enjoy collaborating in person, and the team is working on-site.
• Why you'll enjoy working with Manatal.
• Well-funded start-up backed by Surge & Sequoia.
• Be part of one of the fastest-growing B2B SaaS start-ups in the region.
• You will be collaborating with talented individuals in the industry.
• Join a lively and highly international team.
• Indulge in a challenging and innovative working culture.
• Attractive medical healthcare plan.
• Personal development allowance.
• 2 weeks of work from anywhere per year.
• Regular fun team-building activities.
• Introduction interview with the HR team.
• Introduction interview with CTO and/or Director of Engineering.
• Technical Interview with technical assessment.
• Cultural fit interview with top management team.
• Infrastructure: Amazon Web Services; Kubernetes; GitOps (ArgoCD), GitHub Actions, Terraform, among others.
• Language: Python (Django, FastAPI);.
• Databases: PostgreSQL, MongoDB, Open/ElasticSearch, and Redis, among others;.
• Other: Celery, RabbitMQ, among others.
• Frontend: Typescript (Vue, React).
• Demo Video: https://manatal.wistia.com/medias/vobnq7lvm1.
• Youtube Channel: https://www.youtube.com/channel/Manatal.
• Manatal Hiring: At Manatal, we are dedicated to building an intuitive AI-powered application tracking system to streamline and transform the entire hiring and recruitment process.
• We are devoted to attracting the best talent worldwide to join our team and take pride in being an equal-opportunity workplace. We are committed to equal employment opportunities regardless of religion, race, ethnicity, ancestry, national origin, gender, gender identity, sex, sexual orientation, marital or parental status, disability, age, citizenship or other class protected by applicable law.

ประสบการณ์:

2 ปีขึ้นไป

ทักษะ:

Architecture, Automation, Backbone, Python, DevOps

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:

5 ปีขึ้นไป

ทักษะ:

ETL

ประเภทงาน:

งานประจำ

• Pipeline Development: Design, build, and maintain reliable ETL/ELT pipelines that deliver accurate, complete data from source systems to the data warehouse within agreed timelines.
• Data Modeling: Develop and maintain data models and schemas that are logical, well-organized, and easy for the business to consume.
• Operational Excellence: Keep the platform running: monitor pipeline health, troubleshoot failures fast, and uphold uptime and data availability SLAs.
• Scalability & Efficiency: Build for scale and cost: design solutions that handle growing data volumes without performance degradation, and continuously optimize storage and processing costs.
• Govern and Protect the Data.
• Metadata Management: Maintain data dictionaries and metadata so users across the business can find and understand the information they need.
• Quality Assurance: Implement automated data quality checks (accuracy, completeness, validity) into the pipelines you build, catching issues before they reach decision-makers.
• Compliance: Follow and help enforce the governance framework that protects sensitive company and customer data - supporting our standing target of zero data security incidents and full compliance with PDPA and financial-sector regulations.
• Partner with the Business.
• Requirement Gathering: Sit down with business users to understand their problems and gather requirements - then translate those needs into datasets, pipelines, and data products that actually solve them.
• Proactive Communication: Clarify ambiguous requests, explain trade-offs, and keep stakeholders informed of what's coming and when.
• Data Platform Uptime and Data Availability SLA.
• Data Quality Score across critical datasets.
• Cost Per Terabyte Managed.
• Count of data security incidents (Target: Zero).
• The Ideal Candidate: A Builder Who Owns the Whole ProblemWe are seeking an engineer who doesn't stop at "the pipeline ran." The ideal candidate takes ownership from the business conversation all the way to the delivered dataset: technically strong enough to build robust, scalable pipelines, disciplined enough to document and govern what they build, and communicative enough to work directly with non-technical stakeholders without a translator in between.
• Required Experience & Qualifications.
• Professional Experience: 0-5 years of experience in data engineering, ETL development, or a closely related field. Highly motivated new graduates are strongly encouraged to apply, provided you can demonstrate technical execution through intensive internships, capstone projects, or a robust personal portfolio. Experience in financial services or another regulated industry is a strong advantage.
• Educational Background: A Bachelor's degree in Computer Science, Information Technology, Computer Engineering, Statistics, or a related field.
• Core Technical Skills: Exceptional SQL abilities and solid programming skills (Python preferred). You must have hands-on experience - whether professionally or through rigorous academic/personal projects - building and operating ETL/ELT pipelines and working with data warehouses.
• Valuable Additions: Exposure to cloud data platforms, workflow orchestration tools (e.g., Airflow, Dagster), automated data quality tooling, or data catalog/metadata management.
• Regulatory Awareness: A working knowledge of the Personal Data Protection Act (PDPA) and familiarity with financial-sector regulatory requirements is a plus.
• Essential Qualities & Skills.
• A Builder's Mindset: You are passionate about creating and improving - cleaner pipelines, better models, smarter automation.
• End-to-End Ownership: You chase issues to their root cause and fix them so they stay fixed.
• Analytical Skills: The ability to untangle complex data issues and design solutions that hold up under growth.
• Business Curiosity: You want to know why the business needs the data, not just what columns to deliver.
• Communication: The ability to talk requirements with business users in their language and design with engineers in theirs.
• Meticulous & Disciplined: You document what you build, test what you ship, and treat data quality and security standards as non-negotiable.
• Additional.
• This role is based full-time at our Headquarters in Greater Bangkok - Pak Kret.
• Commitment to Excellence: We need hard workers. We believe that building anything great requires a level of focus and dedication that is incompatible with a conventional "work-life balance." We explicitly reject this mindset because it does not lead to extraordinary outcomes. This is a role for those who are passionate about building something great and are willing to dedicate the long hours required to build a data platform the entire company can trust.
• Compensation and Benefits.
• Your actual level and base salary will be determined on a case-by-case basis and may vary based on job-related knowledge, skills, and experience.
• The base salary is just one part of your total rewards package. You will also receive access to comprehensive benefits, paid leave, and other company perks, which will be discussed during the interview process.
• Equal Opportunity Employer: Our company is an Equal Opportunity Employer; employment is governed on the basis of merit, competence, and qualifications and will not be influenced in any manner by race, religion, gender, disability status, age, sexual orientation, gender identity, or any other legally protected status.

ประสบการณ์:

2 ปีขึ้นไป

ทักษะ:

Analytical Thinking, Data Warehousing, Microsoft Azure, ETL, SQL

ประเภทงาน:

งานประจำ

• Design, develop, implement, and maintain enterprise data integration solutions, data pipelines, and data platform services.
• Manage and support Microsoft Azure data platform components, including Azure Data Factory, Azure Synapse Analytics, Azure Data Lake Storage, and related services.
• Support the adoption, implementation, and continuous improvement of Microsoft Fabric technologies and modern data platform architectures.
• Develop and maintain ETL / ELT processes to ensure reliable movement and availability of business data across enterprise systems.
• Monitor platform performance, availability, capacity, and operational health to ensure service reliability.
• Data Quality and Reliability.
• Establish and maintain data quality controls, validation processes, and reconciliation procedures.
• Investigate, troubleshoot, and resolve data platform incidents, data inconsistencies, and integration failures.
• Monitor and improve data timeliness, accuracy, completeness, and reliability.
• Support business users in identifying, analyzing, and resolving data-related issues.
• Data Governance and Security.
• Maintain data lineage, metadata, data catalogues, and technical documentation for enterprise data assets.
• Support implementation of data governance standards, policies, and best practices.
• Ensure compliance with information security, privacy, and regulatory requirements, including PDPA.
• Implement and maintain appropriate data protection controls, including encryption, access management, data masking, and row-level security.
• Participate in audit, compliance, risk assessment, and remediation activities related to the data platform.
• Business and Vendor Collaboration.
• Collaborate with business units to gather requirements and translate business needs into scalable data solutions.
• Support reporting, analytics, automation, and business intelligence initiatives across the organization.
• Coordinate with external vendors, consultants, and system owners during integrations, upgrades, and project implementations.
• Provide technical guidance and recommendations on data architecture, platform enhancements, and emerging technologies.
• Documentation and Continuous Improvement.
• Develop and maintain technical documentation, architecture diagrams, operational procedures, and support materials.
• Maintain version-controlled repositories and ensure proper documentation of platform configurations and changes.
• Identify opportunities to improve platform performance, scalability, security, reliability, and cost efficiency.
• Continuously develop knowledge and skills related to Microsoft data platform technologies and industry best practices.
• Perform other duties and responsibilities as assigned by management.
• Bachelor's degree or higher in Computer Science, Information Technology, Data Engineering, Computer Engineering, Statistics, or a related field.
• Minimum 2 years of experience in Data Engineering, Data Warehousing, Analytics Engineering, Business Intelligence, or a related technology discipline.
• Experience designing, implementing, and supporting enterprise data platforms and data integration solutions.
• Strong proficiency in SQL and relational database technologies, including data modelling and data warehouse concepts.
• Hands-on experience with Microsoft Azure data services, including Azure Data Factory, Azure Synapse Analytics, and Azure Data Lake Storage.
• Experience developing and maintaining ETL / ELT pipelines for operational reporting, analytics, and business intelligence solutions.
• Understanding of data governance, data lineage, metadata management, and data quality management practices.
• Knowledge of data security principles, including access control, encryption, data masking, and privacy regulations such as PDPA.
• Experience working with Git or other version control platforms for development and configuration management.
• Experience working with business stakeholders to gather requirements and translate them into technical solutions.
• Ability to investigate and resolve complex data platform issues, data quality concerns, and integration failures.
• Strong communication, documentation, analytical thinking, and stakeholder management skills.
• Experience coordinating with external vendors, system integrators, and technology partners is preferred.
• Experience with Microsoft Fabric, Microsoft Purview, hospitality systems, or multi-site operations environments is an advantage.
• Possesses a service-oriented mindset, demonstrates initiative, and continuously seeks opportunities to improve platform reliability, performance, security, and data quality.

ประสบการณ์:

5 ปีขึ้นไป

ทักษะ:

Data Warehousing, Power BI, QlikView, Tableau, Oracle

ประเภทงาน:

งานประจำ

• Design, develop, and implement comprehensive BI solutions, including dashboards, reports, and visualizations, using tools like Power BI, Tableau, or QlikView.
• Develop and maintain complex SQL queries, stored procedures, and ETL processes to ensure data integrity and availability.
• Collaborate with business stakeholders to understand their needs and translate them into technical requirements.
• Design and develop data models and schemas that support reporting and analytics.
• Maintain and optimize the data warehouse environment to ensure performance, scalability, and reliability.
• Implement best practices for data management, data governance, and data security.
• Monitor and enhance the performance of BI solutions by optimizing queries, data models, and ETL processes.
• Troubleshoot and resolve issues related to BI tools, data quality, and data integration.
• Lead and mentor junior BI developers, providing guidance and support on best practices, technical skills, and project execution.
• Work closely with data engineers, analysts, and other IT professionals to ensure data consistency and integrity across the organization.
• Participate in cross-functional teams to deliver BI projects on time and within scope.
• Stay updated with the latest BI trends, tools, and technologies, and evaluate their potential impact on the organization.
• Propose and implement new BI solutions or enhancements to existing ones to improve business processes and decision-making.
• Bachelor's degree in Computer Science, Information Technology, Data Analytics, or a related field.
• 5+ years of experience in business intelligence development, data warehousing, and ETL processes.
• Proficiency in BI tools such as Power BI, Tableau, QlikView, or similar.
• Strong SQL skills and experience with relational databases (e.g., SQL Server, Oracle, MySQL).
• Experience with data modeling tools (e.g., ER/Studio, ERwin).
• Solid understanding of data warehousing concepts, data governance, and data quality best practices.
• Experience with cloud-based BI and data solutions (e.g., Azure, AWS, Google Cloud) is a plus.
• Strong analytical, problem-solving, and critical thinking skills.
• Excellent communication and interpersonal skills, with the ability to work effectively in a team environment.
• Ability to manage multiple tasks and projects simultaneously while meeting deadlines.
• Growth with Tech leader company. Apply here!.

ประสบการณ์:

3 ปีขึ้นไป

ทักษะ:

Power BI, ETL, SQL

ประเภทงาน:

งานประจำ

• Design, develop, and maintain Power BI dashboards, reports, and data models.
• Collaborate with cross-functional teams to understand business requirements and deliver effective BI solutions.
• Partner with Data Engineers, Analysts, and Business Users to ensure data accuracy, performance, and usability.
• Support knowledge-sharing and mentor team members in best practices and new Power BI features.
• Optimize reports for usability and deliver insights in a clear, actionable way.
• Develop and maintain DAX queries, measures, and calculated fields.
• Ensure compliance with data governance, role-based security, and organizational standards.
• Participate actively in team discussions, Agile ceremonies, and problem-solving sessions.
• Bachelor's degree in Computer Science, Information Systems, Data Analytics, or related field.
• 3+ years of experience in Power BI development and data visualization.
• Strong proficiency in DAX, Power Query (M), SQL.
• Experience with data modeling, ETL/ELT, and warehousing concepts.
• Familiarity with cloud platforms (Azure) preferred.
• Experience with CI/CD pipelines for BI solutions is a plus.

ประสบการณ์:

2 ปีขึ้นไป

ทักษะ:

Data Warehousing, Apache, Python, ETL, SQL

ประเภทงาน:

งานประจำ

• Data Pipeline Operations.
• Monitor scheduled and event-driven ETL/ELT pipelines across Azure Data Factory, Databricks, Airflow, and related platforms.
• Investigate failed jobs, delayed data, missing records, schema changes, and dependency issues.
• Rerun or recover pipelines using approved operational procedures and confirm successful completion.
• Support production releases, cutovers, and post-deployment monitoring.
• Incident and Problem Management.
• Respond to data-service incidents and operational requests within agreed service levels.
• Perform root-cause analysis and document the issue, impact, resolution, and preventive action.
• Create, update, and follow operational tickets through closure.
• Coordinate with source-system owners, data engineers, infrastructure teams, and report owners when cross-team support is required.
• Data Quality and Reliability.
• Validate data completeness, accuracy, freshness, and reconciliation results.
• Maintain monitoring, alerting, and operational checks for critical pipelines and datasets.
• Identify recurring failure patterns and recommend permanent fixes or automation.
• Escalate material data risks with clear impact and status communication.
• Stakeholder and Service Support.
• Support users of reports, dashboards, and downstream data products.
• Provide concise updates on incidents, blockers, ownership, and expected next actions.
• Participate in daily operational reviews and handovers.
• Maintain runbooks, troubleshooting guides, support knowledge, and service documentation.
• Continuous Improvement.
• Automate repetitive operational tasks and recovery steps where appropriate.
• Contribute to observability, cost, performance, and reliability improvements.
• Support standardization of deployment, support, and data-quality practices.
• Share lessons learned and help improve team operational readiness.
• Required.
• Bachelor's degree in Computer Science, Information Technology, Data Engineering, or a related discipline, or equivalent practical experience.
• 2-5 years of experience in data engineering, data operations, application support, or production support.
• Hands-on experience supporting production data pipelines or data platforms.
• Strong SQL skills and working knowledge of Python or another scripting language.
• Experience with one or more orchestration or processing technologies such as Azure Data Factory, Databricks, Apache Spark, or Airflow.
• Understanding of data warehousing, ETL/ELT, file and database integration, job dependencies, and data-quality controls.
• Ability to troubleshoot methodically, communicate clearly, and work across technical and business teams.
• Experience with Azure or AWS data services.
• Experience with Linux, shell scripting, Git, and CI/CD practices.
• Familiarity with monitoring platforms such as Azure Monitor, CloudWatch, Grafana, or equivalent tools.
• Experience with Jira or an IT service-management platform.
• Retail, e-commerce, finance, supply-chain, or enterprise analytics experience.
• Knowledge of access controls, secrets management, and secure production-support practices.
• Production ownership and service mindset.
• Structured troubleshooting and root-cause analysis.
• Attention to data quality and operational detail.
• Clear incident communication and stakeholder coordination.
• Prioritization under pressure.
• Continuous improvement and automation mindset.

ทักษะ:

Python, SQL, English

ประเภทงาน:

งานพาร์ทไทม์

• Participate in designing and implementing as well as maintaining data pipelines for digesting data from various marketplaces into Data Platform.
• Demonstrate continuous improvement by inspecting and adopting new ideas for improving solutions, tools and processes.
• Work closely with members of IT (e.g. Architecture, DevOps and Business Analysts) to ensure the highest quality softwareCoach fellow associate data engineers.
• Capabilities.
• Bachelor Degree from Computer Engineering, Computer Science or related fields.
• Good knowledge of SQL, relational database design and efficient methods for working with large size of data.
• Good knowledge of Python.
• Understanding of fundamental design principles behind data-oriented application.
• Ability to understand business requirements and be able to express them in computer language.
• Ability to communicate in English, both written and oral form.

ประสบการณ์:

5 ปีขึ้นไป

ทักษะ:

Financial Reporting, ERP, ETL, Data Warehousing, Oracle

ประเภทงาน:

งานประจำ

• Bangkok, Thailand.
• Full-time.
• Workplace: on_site.
• Department: Technology.
• The Senior Data Engineer I sits within the Finance Transformation team in IT at CP Axtra, responsible for the end-to-end data engineering that powers financial reporting, planning, and analytics across Makro and Lotus's. He/she designs and operates the data pipelines feeding Oracle Fusion (ERP/EPM) and the enterprise data platform, ensuring finance data is available, accurate, and reliable to enable data-driven decisions for the CFO organization.
• Lead and mentor the data engineering effort, fostering collaboration, innovation, and continuous learning within Finance Transformation.
• Oversee the design, development, and maintenance of scalable, efficient data pipelines supporting financial reporting, planning, and analytics.
• Build and maintain integrations between Oracle Fusion (ERP/EPM) and the enterprise data platform to deliver trusted finance data.
• Collaborate with data scientists, analysts, FP&A, and Finance stakeholders to understand requirements and ensure seamless data integration.
• Implement data quality, reconciliation, and validation checks to ensure the accuracy, completeness, and reliability of financial data sets.
• Design data architecture that supports current and future finance needs, considering scalability, performance, and auditability.
• Evaluate and select appropriate tools and technologies to enhance data processing, storage, and analytics capabilities.
• Optimize pipelines for performance and efficiency, considering data volume, processing speed, and month-end close deadlines.
• Implement data governance and controls to ensure compliance with financial controls, audit requirements, and data privacy (PDPA).
• Stay updated with emerging data engineering trends and apply them to improve the team's finance data capabilities.
• Master's or Bachelor's degree in Computer Science, Engineering, or a related field.
• 5-8 years in data engineering, including building pipelines for finance, ERP, or transactional data.
• Strong expertise in ETL/ELT, data warehousing, and data integration with ERP systems such as Oracle Fusion.
• Proficiency in Python and SQL, with big data technologies (e.g., Spark/Databricks) and cloud data platforms.
• Experience with data modeling, dimensional design, and optimizing storage for financial reporting and reconciliation.
• Strong problem-solving skills to diagnose and resolve data quality and pipeline issues affecting financial figures.
• Excellent communication skills to work with Finance, Accounting, and FP&A stakeholders alongside technical teams.
• Familiarity with Agile/Scrum, data governance, and data privacy (e.g., Thailand PDPA) in a finance context.
• International workplace.
• Opportunities for growth in e-commerce, wholesales, and retail industry.
• Competitive benefits.
• Fast-paced, dynamic, and supportive environment.
• Apply.
• Apply at CP Axtra](https://apply.workable.com/joinmakropro/j/D3DA891695/apply).

ทักษะ:

Big Data, ETL

ประเภทงาน:

งานประจำ

• Maintain data dictionary, relationship and its interpretation.
• Analyze problem and find resolution, as well as work closely with administrators to monitor performance and advise any necessary infrastructure changes.
• Work with business domain experts, data scientists and application developers to identify data that is relevant for analysis.
• Develop big data solutions for batch processing and near real-time streaming.
• Own end-to-end data ETL/ELT process framework from Data Source to Data warehouse.
• Select and integrate appropriate tools and frameworks required to provide requested capabilities.
• Design and develop BI solutions.
• Hands-on development mentality, with a willingness to troubleshoot and solve complex problems.
• Keep abreast of new developments in the big data ecosystem and learn new technologies.
• Ability to effectively work independently and handle multiple priorities.

ประสบการณ์:

5 ปีขึ้นไป

ทักษะ:

Big Data, Cloud Computing, ETL, Python, Java

ประเภทงาน:

งานประจำ

• Nawamin Road, Thailand (Hybrid).
• Workplace: hybrid.
• We are seeking an experienced Senior Data Engineer to design, implement, and maintain our data infrastructure and pipelines. The ideal candidate will have a strong background in data engineering, big data technologies, and cloud platforms. You will work closely with data scientists, analysts, and other stakeholders to ensure efficient and reliable data processing and storage solutions.
• Design, develop, and maintain scalable data pipelines and ETL processes.
• Implement and optimize data storage solutions, including data warehouses and data lakes.
• Collaborate with data scientists and analysts to understand data requirements and provide efficient data access.
• Ensure data quality, consistency, and reliability across all data systems.
• Develop and maintain data models and schemas.
• Implement data security and access control measures.
• Optimize query performance and data retrieval processes.
• Evaluate and integrate new data technologies and tools.
• Mentor junior data engineers and provide technical leadership.
• Collaborate with cross-functional teams to support data-driven decision-making.
• Bachelor's or Master's degree in.
• Computer Science, Engineering., or a related field.
• 5+ years of experience in data engineering or related roles.
• Strong programming skills in Python, Java, or Scala.
• Extensive experience with big data technologies such as Hadoop, Spark, and Hive.
• Proficiency in.
• SQL.
• and experience with both relational and NoSQL databases.
• Experience with cloud platforms (AWS, Azure, or GCP) and their data services.
• Knowledge of data modeling, data warehousing, and ETL best practices.
• Familiarity with data visualization tools (e.g., Tableau, Power Bl).
• Experience with version control systems (e.g., Git) and CI/CD pipelines.
• Strong problem-solving skills and attention to detail.
• Excellent communication and collaboration skills.
• Additional.
• Preferred.
• Experience with stream processing technologies (e.g., Kafka, Flink).
• Knowledge of machine learning and Al technologies.
• Familiarity with data governance and compliance requirements.
• Experience with containerization and orchestration tools (e.g., Docker, Kubernetes).
• Contributions to open-source projects or relevant certifications.
• Experience in Azure big data platform (ADF, Databrick).
• Experience in PowerBl.
• Apply.
• Apply at CP Axtra](https://apply.workable.com/joinmakropro/j/72AC50884D/apply).

ประสบการณ์:

3 ปีขึ้นไป

ทักษะ:

Teamwork, Big Data, Kafka, Cloud Computing, SQL

ประเภทงาน:

งานประจำ

• Design, build, and maintain data pipelines and infrastructure to support data-driven initiatives.
• Collaborate with data scientists, analysts, and other stakeholders to understand data requirements and deliver scalable solutions.
• Develop and maintain data models, data dictionaries, and data transformation processes.
• Monitor and troubleshoot data pipelines to ensure data quality and availability.
• Implement and maintain data security and privacy measures.
• Continuously evaluate and improve data systems to optimize performance and scalability.
• Keep up-to-date with industry trends and best practices in data engineering and apply them to our data systems.
• Mentor and train junior data engineers on data engineering best practices and technologies.
• Bachelor's degree in Computer Science, Information Systems, or a related field.
• Minimum of 3 years of experience in data engineering.
• Strong experience with Databricks and other big data technologies such as PySpark, and Kafka.
• Proficient in SQL and experience with data modeling and ETL processes.
• Experience with cloud platforms such as AWS or Azure.
• Knowledge of data security and privacy principles.
• Strong problem-solving and analytical skills.
• Excellent communication and teamwork abilities.
• Proven ability to work in a fast-paced and dynamic environment.
• Why Join Us?.
• Opportunity to work with cutting-edge technologies and innovative solutions.
• Dynamic and collaborative work environment.
• Competitive salary and benefits package.
• Career growth and development opportunities.
• Work-life balance and flexible working hours.
• Fun and inclusive company culture.
• If you are passionate about data engineering and want to be a part of a dynamic team that is driving innovation in Thailand, then we want to hear from you. Apply now to join Gosoft(Thailand)Co.,Ltd. as a Data Engineer and take your career to the next level.

ทักษะ:

Data Analysis, Architecture, Big Data

ประเภทงาน:

งานประจำ

• Build and maintain data pipelines to collect, transform, and store data from robotic systems and sensors.
• Design data architecture to support real-time and historical data analysis.
• Implement ETL processes and ensure data quality, validation, and monitoring.
• Optimize database performance and manage large-scale data storage (structured and unstructured).
• Collaborate with AI, robotics, and software teams to align data workflows with operational needs.
• Maintain data documentation and ensure compliance with data privacy and security standards.
• Demonstrate a commitment to improve and comply with SSHE policy, environment regulations as well as labor law.
• Perform other related duties as assigned.
• Skills and Abilities.
• Excellent analytical and problem-solving skills.
• Understanding about metadata and data governance.
• Familiar with a variety of software patterns and principles.
• Understanding of big data architecture and streaming analytics.
• Has a good understanding of software engineering principles.
• Experience designing software applications running on multiple platform types.
• Experience in evaluating machine learning applications.
• Ability to effectively communicate product architectures, design proposals and negotiate options at management levels.
• Competencies.
• I DREAM - Passion.
• I DREAM - Fun.
• I DARE - Innovate.
• I DARE - Drive Result.
• WE DO - Respect.
• WE DO - Teamwork.