M11 - Data Engineer

FPT Asia Pacific; Singapore; On-site; SGD 90,000 - 120,000; Full time

Job summary

FPT Asia Pacific is seeking a data engineer to design, develop, and maintain data pipelines that source from diverse formats, transform per business rules, and load into target systems.

You will perform data extraction, cleaning, transformation, and flow, and build scalable batch and real-time pipelines using modern frameworks. Collaboration with cross-functional teams is essential.

Qualifications

• Bachelor's degree in Computer Science, Software Engineering, or related field.
• At least 3–5 years experience in ETL/data integration projects.
• Proficient in data cleaning and transformation using SQL, Python (R a plus).
• Proficient in building ETL pipelines (SSIS, Python, Snowflake) with cloud tools (AWS/Azure).
• Hands-on experience with SSIS and Snowflake; strong DB design skills.

Responsibilities

• Design, develop, and maintain data pipelines extracting from multiple sources.
• Perform data extraction, cleaning, transformation, and flow.
• Build large-scale batch and real-time data pipelines with processing frameworks.
• Integrate data silos ensuring scalability and compliance.
• Collaborate with PM, Data Architect, BAs, frontend developers, and analysts.

Skills

SQL

Python

ETL/ELT

Data pipelines

CI/CD

Education

Bachelor's degree in CS/SE

Tools

SSIS

Snowflake

AWS

Azure

GitLab

Ansible

Job description

• Design, develop, and maintain data pipelines that extract data from various sources and formats, transform it according to business requirements, and load it into target systems.
• Perform data extraction, cleaning, transformation, and flow.
• Design, build, launch and maintain efficient and reliable large-scale batch and real-time data pipelines with data processing frameworks.
• Integrate and collate data silos in a manner which is both scalable and compliant.
• Collaborate with the Project Manager, Data Architect, Business Analysts, Frontend Developers, Designers and Data Analysts to build scalable data driven products.
• Work in an Agile Environment that practices Continuous Integration and Delivery.
• Work closely with fellow developers through pair programming and code review process.

Requirements

• Bachelor's degree in Computer Science, Software Engineering, or related field.
• At least 3–5 years experience in ETL/data integration projects.
• Proficient in general data cleaning and transformation using scripting languages (mandatory: SQL, Python; added advantages: R, etc) to ensure data accuracy and consistency. Knowledge in R will be an advantage.
• Proficient in building ETL pipeline (mandatory: SQL Server Integration Services SSIS, Python, Snowflake; added advantages: AWS Lambda, ECS Container task, Eventbridge, AWS Glue, Spring, etc).
• Proven hands‑on experience with Microsoft SSIS and Snowflake.
• Proficient in database design and various databases (mandatory: SQL, AWS S3, RDS; added advantages: PostgreSQL, Athena, MongoDB, Postgres/GIS, MySQL, SQLite, VoltDB, Apache Cassandra, etc).
• Experience in cloud technologies such as GCC and GCC+ (i.e. AWS, Azure).
• Experience in and passion for data engineering in a big data environment using Cloud platforms such as GCC and GCC+ (i.e. AWS, Azure).
• Experience in building production‑grade data pipelines, ETL/ELT data integration.
• Experience in CI/CD pipelines and DevOps tools (e.g. GitLab).
• Experience in automated provisioning tools (Ansible, Terraform, Puppet, Vagrant) will be an advantage.
• Familiar with data modelling, data access, and data storage infrastructure like Data Mart, Data Lake, Data Virtualisation and Data Warehouse for efficient storage and retrieval.
• Familiar with REST API and web requests/protocols in general.
• Familiar with data governance policies, access control and security best practices.
• Knowledge of system design, data structure and algorithms.
• Knowledge of AI/ML RAG (Retrieval-Augmented Generation), MCP (Model Context Protocol) concepts.
• Comfortable in both Windows and Linux development environments.
• Interest in being the bridge between engineering and analytics.