เงื่อนไขการค้นหา

ทักษะ:

ETL, Big Data

ประเภทงาน:

งานประจำ

• Pipeline Development: Support the design and maintenance of scalable ETL/ELT pipelines for structured and unstructured datasets..
• AI Data Readiness: Assist in building data ingestion flows for Vector Databases and supporting RAG (Retrieval-Augmented Generation) architectures..
• Data Modeling: Contribute to the creation of robust data models and Feature Stores that serve both traditional analytics and machine learning workloads..
• Data Quality & Operations.
• Validation & Cleaning: Implement automated scripts to ensure high data integrity, reliability, and performance across the platform..
• Cloud Optimization: Assist in monitoring cloud resource usage (GCP/AWS) to ensure cost-efficiency and low-latency data access..
• Engineering Collaboration: Work closely with senior engineers to document data lineage and ensure the architecture is built for long-term scalability..
• Experience: Entry-level to 2 years of experience in data engineering, backend development, or a related technical internship.
• Portfolio: Demonstration of coding ability through a Github repository or a portfolio of data projects (e.g., building a personal API, a data scraper, or a small-scale ETL project)..
• Education: Bachelor s degree in Computer Engineering, Computer Science, Statistics, or a related technical field..
• Python: Solid foundation in writing clean, modular Python code.
• SQL: Proficiency in writing and optimizing complex queries for data analysis.
• Cloud Knowledge: Familiarity with at least one major cloud provider (GCP or AWS) and basic understanding of services like BigQuery, Redshift, or S3.
• AI Awareness: Interest in how data engineering supports AI; basic knowledge of unstructured data or vector search is a plus..
• What We Offer.
• Hands-on Multi-Cloud Experience: Get direct exposure to large-scale data environments on GCP/AWS and modern orchestration tools..
• Innovative Tech Stack: Work with cutting-edge tools at the intersection of Big Data and AI, including Vector DBs and automated data quality frameworks..
• Growth & Mentorship: A supportive environment where you will learn from senior engineers and have a clear path for professional development..
• Impactful Work: See your data pipelines directly power real-time marketing decisions and AI-driven products..
• If you re ready to build the data foundation for the next generation of AI, apply now!.

ทักษะ:

SQL, ETL, Project Management, English

ประเภทงาน:

งานประจำ

• Consolidate requirements from various business functions and create common business data models within data warehouse for each business function to serve business needs.
• Working with Data Governance, Data Management, and Data Engineering team to setup data warehouse model and working with business users to develop data marts.
• Assessing the effectiveness and accuracy of data sources and data gathering techniques.
• Applying strong expertise in business intelligence skills set to develop customized and innovative solutions.
• Developing best practice for analytic and business intelligence solutions.
• Working with the IT function and project leaders in providing technical guidance regarding data architecture, data models and data management and translate business needs into requirements for analytics and business intelligence solutions.
• Always stay on latest data and BI technologies.
• Designs and develops BI relevant solutions, data model, data mart, data warehouse, report, and dashboard.
• Professional Knowledge & Experiences.
• A bachelor s degree in computer science, engineering or IT related field.
• Proficient knowledge of SQL and Relational Database, knowledge on google cloud is a plus.
• Experience in any ETL, data mart, data warehouse, data modeling design.
• Experience in any BI visualize tools, PowerBI or TIBCO Spotfire is a plus.
• Experience working with Product Owners or Business users to understand business needs, define scope and translating requirements into technical specifications.
• Strong problem-solving skills.
• A drive to learn.
• A good command of the English language.
• Preferably experience and skills in project management.
• Preferably a knowledge of or a background in the oil & gas industry.
• Additional Desirable Qualification.
• CORE Competencies.

ทักษะ:

ETL, Compliance, SQL

ประเภทงาน:

งานประจำ

• Design, implement, and manage end-to-end data pipelines architectures.
• Configure and maintain data ingest workflows (ETL) across several production systems.
• Transform data into Data Mart, Data Model that can be easily analyzed.
• Ensure data accuracy, high usability, timely availability, and strong performance.
• Demonstrate a hands-on development mindset with a willingness to troubleshoot and solve complex problems.
• Ensure compliance with data governance and security policies.
• Minimum of 3 years of work experience as a Data Engineer.
• Strong SQL skills with knowledge of NoSQL tools and languages.
• Strong proficiency in Python scripting.
• Experience with AWS Cloud Data Platform services such as S3, Redshift, Glue, Step Functions, and Lambda.
• Experience with other cloud data platforms such as GCP or Azure is an advantage.
• Experience working on Big Data platform is an advantage.
• Strong business understanding, with the ability to identify business problems, define business goals, and locate relevant data.

ประเภทงาน:

งานประจำ

• The Senior Data Engineer position plays a key role in designing, developing, and managing cloud-based data platforms, as well as creating data structures for high-level data analysis, and works with business and technical teams to ensure that data management is appropriate and supports organizational goals.
• Responsible for the design, construction, and maintenance of optimal and scalable data pipeline architectures on cloud platforms (e.g., GCP, AWS, Azure).
• Oversee the development and management of complex ETL/ELT processes for data ingesti ...
• Author and optimize advanced, high-performance SQL queries for complex data transformation, aggregation, and analysis.
• Leverage the Python programming language for automation, scripting, and the development of data processing frameworks.
• Administer and optimize cloud-based data warehouse solutions and associated data lakes.
• Collaborate professionally with data scientists, analysts, and key business stakeholders to ascertain data requirements and deliver effective technical solutions.
• Provide mentorship to junior engineers and champion the adoption of data engineering best practices throughout the organization.
• Bachelor s degree or higher in Computer Science, Information Technology, Engineering, or a related field.
• At least 5 years of experience working in a data engineering or related position.
• Proficient in advanced SQL, including query optimization and performance tuning.
• Experienced in managing and designing architecture on at least one major cloud platform (Google Cloud Platform, AWS, or Azure).
• Skilled in using Python for data processing and advanced pipeline development.
• Experienced with tools and technologies for data ingestion, connectivity, and management.
• Deep understanding of data modeling principles, data warehousing methodologies, and modern data architecture.
• Excellent analytical and problem-solving skills.
• Communication and teamwork skills.
• Ability to plan and manage tasks effectively.

ทักษะ:

ETL, Product Development, Power BI

ประเภทงาน:

งานประจำ

• Bachelor's degree in Computer Science, Data Science, Business Analytics, or related field; Master's preferred.
• 1-5 years of experience in product management, least 1 years focused on data products.
• Demonstrated experience with data platforms, analytics tools, and data visualization technologies.
• Strong understanding of data modeling, ETL processes, and database architectures.
• Experience with agile methodologies and product development lifecycle.
• Ability to translate complex technical concepts to non-technical audiences.
• Familiarity with BI tools (Power BI, Tableau, Looker, etc.).
• Contact Information K. Nanchanok Ratsamesuntarangkul
• Email: nanchanok.r @thaibev.com
• Company name: DIGITAL AND TECHNOLOGY SERVICES CO., LTD.
• Working Location and address: F.Y.I Center 2525 Rama IV Rd, Khlong Tan, Khlong Toei, Bangkok 10110
• MRT QSNCC Station Exit 1.

ทักษะ:

ETL

ประเภทงาน:

งานประจำ

• Design and deliver cloud-native banking solutions on AWS.
• Build rapid prototypes and live demos for client engagements.
• Integrate AI and data capabilities into core banking platforms.
• The ideal candidate combines strong engineering depth, banking domain expertise, and the ability to translate ideas into working solutions quickly.
• Core Banking Transformation.
• Lending / loan origination and servicing.
• Credit decisioning systems.
• Payments, deposits, and investment platforms.
• Legacy cloud-native (rehost, replatform, refactor).
• Monolith microservices / event-driven architecture.
• Translate business requirements into scalable, secure, production-ready architectures.
• Client-Facing Demo & Prototyping (Critical Requirement).
• Build end-to-end functional prototypes and demos on AWS to showcase solutions.
• Working applications.
• API-driven services.
• AI/data-driven proof-of-value solutions.
• Solution workshops.
• Pre-sales discussions.
• Live demo sessions with business and technology stakeholders.
• Expected capability: Build a working demo (e.g., AI-powered credit workflow or customer 360 solution) within short timelines.
• AWS Cloud Engineering (Hands-on Senior Level).
• Architecture & Design.
• Microservices and event-driven patterns.
• API-first integration models.
• High availability, scalability, and resiliency.
• Security and regulatory compliance.
• Core AWS Stack.
• Compute: Lambda, ECS/EKS, EC2.
• Data: S3, Aurora/RDS, DynamoDB.
• Integration: API Gateway, Step Functions, EventBridge.
• Observability: CloudWatch and monitoring frameworks.
• DevOps & Automation.
• Infrastructure-as-Code (Terraform / CloudFormation / CDK).
• CI/CD pipelines and automated deployment.
• Ability to stand up environments quickly for demos and delivery.
• AI & Data Capabilities in Banking (Strong Preference).
• Data Engineering.
• Data lakes (S3-based architectures).
• ETL / ELT pipelines.
• Customer, transaction, credit, and risk datasets.
• Machine Learning & Analytics.
• Credit scoring and underwriting.
• Fraud detection / AML.
• Customer segmentation and personalization.
• GenAI & Modern AI.
• RAG-based solutions (e.g., document processing, KYC).
• AI assistants for banking users.
• AWS Bedrock / SageMaker / equivalent.
• LLM orchestration and vector search.
• Real-Time Decisioning.
• Real-time credit approvals.
• Fraud detection and alerts.
• Client Engagement & Thought Leadership.
• Act as a trusted technical advisor to financial services clients.
• Architecture discussions.
• Solution design workshops.
• Pre-sales and technical solutioning.
• Core banking modernization.
• Cloud + AI transformation.
• Bridge business, data, and technology stakeholders effectively.
• Banking technology / financial services IT.
• Core banking systems (lending, payments, deposits, investments).
• Core banking modernization or migration programs.
• Large-scale transformation initiatives.
• Cloud-native architecture and development.
• Microservices / distributed systems.
• Strong hands-on programming experience in Python (preferred), with the ability to build cloud-native applications, data pipelines, and rapid client-facing prototypes.
• Build working demos / PoCs under time pressure.
• Operate effectively in client-facing roles..
• Preferred Qualifications.
• Temenos, Mambu, Finacle, FLEXCUBE, nCino.
• Data engineering and analytics platforms.
• ML / GenAI use cases integrated into business workflows.
• Event-driven architecture.
• API-first ecosystems.
• Domain-driven design (DDD).
• AWS Certifications (Associate / Professional).
• Profile We Are Targeting.
• Hands-on builder (not a pure architect or program manager).
• Able to design, build, and demo solutions live to clients.
• Strong banking domain credibility.
• Bridges cloud + core banking + AI/data.
• Comfortable in pre-sales + delivery hybrid environments..