Data Engineering & Platform Development

Design and develop scalable and reliable data pipelines.
Build enterprise data platforms, including data warehouses, data lakes, and lakehouses.
Implement cloud, hybrid, and on-premises data architectures aligned with enterprise standards.

ETL/ELT & Data Integration

Data Management & Governance

Design and manage data storage solutions with a strong focus on object storage, data quality, and data governance.
Implement and maintain data lifecycle management and cost-optimisation strategies.
Ensure data lineage, traceability, and auditability.

Analytics & BI Enablement

Engineer analytics-ready data models for reporting and self-service analytics.
Enable BI dashboards, reports, and analytics through performant and governed data pipelines.

Security & Compliance

Ensure compliance with government security and privacy requirements.
Implement and maintain encryption, access controls, secure data handling practices, and system security policies.

Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related field.
Minimum 3 years of experience in enterprise data engineering roles.
Strong hands-on data engineering experience.
Strong SQL and Python skills.
Experience with ETL/ELT tools, with Talend highly preferred.
Experience with data warehouses, data lakehouses, data lakes, and object storage systems.
Qlik Sense Enterprise integration experience is highly preferred.
Prior CAT 1 / G50 security clearance is required.
Previous experience delivering MINDEF projects is required.

Data Engineer AMK