Senior Assistant Director (Data Engineer), DTID

Agency for Science, Technology and Research (A*STAR); Singapore; On-site; SGD 90,000 - 120,000; Full time

Job summary

A leading research institute in Singapore is seeking a Senior Assistant Director (Data Engineer) to design and maintain the enterprise data architecture. This role requires optimizing data pipelines using Azure Data Factory and Snowflake and ensuring compliance with public-sector standards. The ideal candidate will have 8-10 years of experience in data engineering, a Bachelor's degree, and proficiency in SQL and Python. Mentorship of junior engineers is also a key responsibility. This position offers a chance to drive innovation in data practices.

Qualifications

• 8 to 10 years of experience in data engineering or platform development.
• Hands-on experience with Snowflake and Azure Data Factory.
• Strong knowledge of data modeling and cloud-warehouse architecture.

Responsibilities

• Design and implement data pipelines using ADF and best practices.
• Build and optimize data marts for analytics tools like Power BI.
• Integrate metadata into Alation for enhancing data discoverability.
• Mentor junior engineers on best practices in data architecture.

Skills

Data pipeline design

Snowflake optimization

SQL proficiency

Python programming

ETL/ELT practices

Data orchestration tools

Collaboration skills

Education

Bachelor's Degree in Computer Science or related discipline

Tools

Azure Data Factory

Snowflake

Alation

Airflow

Job description

The Digital Transformation, Innovation and Data Division helps the organisation make better decisions, work efficiently, and innovate confidently by improving data use, developing business intelligence, and enabling responsible AI adoption.

The Senior Assistant Director (Data Engineer) designs, builds, and maintains the organisation's enterprise data architecture.

This role ensures that data across HQ and Research Institutes is reliable, secure, and analytics-ready. The Senior Assistant Director (Data Engineer) also drives standards, performance optimisation, and automation for scalable analytics and AI delivery.

Key Responsibilities

A. Data Architecture & Engineering

• Design and implement robust data pipelines using Azure Data Factory (ADF) and ELT/ETL best practices.
• Build and optimise data marts to support enterprise dashboards and analytics tools (e.g., Power BI).
• Optimise Snowflake environments for performance, cost, and scalability.
• Partner with IT Shared Services to ensure compliance with IM8, PDPA, and enterprise security standards.

B. Platform Administration & Automation

• Administer Snowflake accounts, roles, warehouses, and data-sharing configurations.
• Integrate metadata and lineage flows into Alation to enhance discoverability and governance.
• Implement automation pipelines and CI/CD practices for ingestion, validation, and deployment.

C. Data Quality & Reliability

• Develop and maintain validation checks, profiling, and error-handling logic within pipelines.
• Collaborate with Data Analysts and Scientists to ensure datasets meet analytical and AI model requirements.

D. Collaboration & Mentorship

• Partner with Business Analysts and the AI team to operationalise dashboards and machine-learning outputs.
• Mentor junior engineers in coding, documentation, and data-architecture best practices.

Qualifications & Experience

• Bachelor's Degree in Computer Science, Data Engineering, Information Technology, or a related discipline.
• At least 8 to 10 years of experience in data engineering or platform development roles.
• Hands on experience with Snowflake, Azure Data Factory, and metadata catalogues (e.g., Alation, Collibra).
• Proficient in SQL, Python, and data-orchestration tools (e.g., Airflow, dbt).
• Strong knowledge of data modelling, cloud-warehouse architecture, and CI/CD automation.
• Familiar with public-sector data governance and compliance (IM8, PDPA).
• Demonstrated ability to collaborate across analytics, AI, and IT teams.