(What the role is)
A hands-on technical role responsible for designing, building, and maintaining the data pipelines and infrastructure that power IMDA's Data Platforms. The role sits at the intersection of data engineering and applied data science, and is critical to enabling data-driven decisions and AI-ready capabilities across the organisation.
(What you will be working on)
Design, build, and maintain scalable and reliable data pipelines for both batch and real-time data processing
Contribute to data modelling and architecture decisions, including schema design and data warehouse or lakehouse structures
Apply data science knowledge to support data quality, anomaly detection, and preparation of AI-ready datasets
Collaborate with data analysts, product owners, and business stakeholders to translate requirements into robust data solutions
Ensure pipelines and data storage practices comply with IM8 and other regulatory requirements, including data governance and cataloguing practices
Champion documentation practices and platform operability across the team
Provide technical guidance and mentoring to junior team members
(What we are looking for)
Minimum 5 years of data engineering experience with a strong track record in production data pipeline delivery
Data science background — working knowledge of statistical analysis, ML concepts, and experience preparing datasets for analytical or ML use cases
Proficiency in Python and SQL; experience with pipeline frameworks such as Apache Spark or Airflow
Experience with cloud platforms; familiarity with GCC or equivalent government-certified environments preferred
Strong communication skills and comfortable working in an agile, fast-paced environment
Experience with robotics, IoT sensor, or real-time streaming data
Familiarity with MLOps practices and tools
Experience with data cataloguing or governance tools
Only shortlisted candidates will be notified.
Position will commensurate with experience.