M27 - Data Engineer

FPT Asia Pacific Pte Ltd; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

FPT Asia Pacific Pte Ltd is seeking a Senior Data Engineer to design, build and operate enterprise-grade data systems supporting analytics and digital products. You will shape architecture, establish robust practices, and accelerate technical decision-making.

You will design scalable data pipelines, develop data models, and apply engineering standards to improve reliability and security. Cross-functional collaboration and technical mentorship are key aspects of the role.

Qualifications

• Strong Python and SQL development skills in production data systems.
• Strong experience in enterprise data architecture and engineering, applying patterns to problems.
• Experience designing data pipelines and data models for data warehouses, lakes and lakehouse architectures.
• Experience with cloud platforms, preferably AWS, and modern data platforms like Redshift, Snowflake, Databricks, BigQuery or equivalent.
• Experience with data orchestration, transformation and modeling using modern engineering tools.
• Solid production engineering practices including testing, CI/CD, monitoring and data quality.

Responsibilities

• Design, build and operate scalable data architectures and pipelines across diverse data sources and use cases.
• Develop robust data models and reusable data capabilities for analysts, data scientists and other data consumers.
• Apply architectural and engineering practices to improve reliability, security, observability, performance and maintainability of data systems.
• Evaluate technologies and approaches, and contribute to the Data Programme's architecture and standards.
• Champion modern software engineering practices including automated testing, code reviews, CI/CD and infrastructure-as-code.
• Collaborate cross-functionally with engineers, Product Managers and data users, providing technical leadership and mentoring.

Skills

Python

SQL

Data architecture

Data pipelines

Data modeling

AWS

Data warehouses

Lakehouse architectures

CI/CD

Data observability

Metadata catalog

Apache Spark

Airflow

dbt

Tableau

Power BI

Tools

Airflow

dbt

Apache Spark

Tableau

Power BI

AWS

Job description

Responsibilities

As a Senior Data Engineer on Data Programme, you will design, build and operate enterprise-grade data systems and platforms supporting analytics, data science and digital products. You will bring experience from complex data environments to help shape architecture, establish robust engineering practices and accelerate technical decision-making.

You will be expected to:

• Design, build and operate scalable data architectures and pipelines for ingesting, transforming and serving data across diverse source systems and use cases.
• Develop robust data models and reusable data capabilities for applications, analysts, data scientists and other data consumers.
• Apply proven architectural and engineering practices to improve the reliability, security, observability, performance and maintainability of data systems.
• Evaluate technologies and architectural approaches, make sound technical trade-offs, and contribute to the evolution of the Data Programme's architecture and engineering standards.
• Champion modern software engineering practices, including automated testing, code review, CI/CD and infrastructure-as-code, and help the team consistently meet these standards through review and coaching.
• Work cross-functionally with engineers, Product Managers, Data Scientists, analysts and users, while providing technical leadership through design reviews, mentoring and knowledge sharing.

What We Are Looking For

• Strong software engineering fundamentals and proficiency in Python and SQL, with hands-on experience building and operating complex production data systems.
• Strong experience in enterprise data architecture and engineering, with the ability to apply established patterns and practices to new technical problems.
• Experience designing data pipelines and data models, with a strong understanding of data warehouses, data lakes and lakehouse architectures.
• Experience with cloud platforms, preferably AWS, and modern data warehouse or data platforms such as Redshift, Snowflake, Databricks, BigQuery or equivalent.
• Experience with data orchestration, transformation and modelling using modern engineering approaches and tools.
• Strong understanding of production engineering practices, including testing, CI/CD, monitoring, troubleshooting and data quality.

Good to Have

• Hands-on experience with workflow orchestration tools such as Apache Airflow or equivalent.
• Experience with transformation and analytics engineering frameworks such as dbt or equivalent.
• Experience with distributed data processing technologies such as Apache Spark.
• Deep experience with AWS data services and cloud infrastructure.
• Familiarity with BI and analytics tools such as Tableau, Power BI or equivalent.
• Experience with infrastructure-as-code, data observability, metadata, catalogue or lineage capabilities.
• Experience working with sensitive or regulated data, and an interest in using technology and data for public good.