Data Engineer (GeBIZ X)
Summary
Build and maintain scalable data pipelines and AI-driven platforms for Singapore’s government procurement system, integrating ETL, streaming, and MLOps to support public-sector decision-making.
Data Engineer (GeBIZ X) at GovTech
About the role GovTech is seeking a Data Engineer to build enterprise-grade platforms for GeBIZ X, the Ministry of Finance initiative transforming government procurement. You will design scalable data pipelines and integrate AI-driven capabilities to improve decision-making across the public sector. This role involves collaborating with diverse teams to translate complex business needs into functional data products.
Key facts
- Location: Singapore
- Engagement: 2-year fixed term contract
- Team: GeBIZ X
What you'll do
- Design and maintain scalable data platforms, pipelines, and reusable datasets.
- Implement ETL and ELT processes for both structured and unstructured data.
- Develop machine learning and LLM-based solutions, including prompt engineering and MLOps.
- Apply advanced integration techniques such as streaming, message queues, and Change Data Capture.
- Champion DataOps practices, including automated deployments, monitoring, and data observability.
- Ensure data systems comply with security, privacy, and regulatory standards.
- Mentor junior team members and conduct code reviews to maintain engineering quality.
Requirements
- Bachelor degree or higher in Computer Science, Data Science, Statistics, Applied Mathematics, or a related quantitative field.
- Minimum 5 years of professional experience in data engineering.
- Proven track record of delivering data products within large-scale enterprise environments.
- Expertise in data modelling for OLTP and OLAP systems.
- Proficiency in Python, Scala, or Java.
- Experience with cloud data platforms like AWS, Azure Synapse, Microsoft Fabric, Snowflake, Databricks, or Redshift.
- Knowledge of big data technologies such as Spark, Kafka, Flink, or Hadoop.
- Familiarity with CI/CD and DataOps practices like SHIP-HATS.
Nice to have
- Understanding of machine learning concepts and LLM application development.
- Experience with MLOps practices and cloud-based model deployment.
- Knowledge of responsible AI principles regarding safety and fairness.
Skills & tools
- Data Modelling (OLTP, OLAP, Dimensional)
- Python, Scala, Java
- AWS, Azure Synapse, Microsoft Fabric, Snowflake, Databricks, Redshift
- Spark, Kafka, Flink, Hadoop
- ETL/ELT, Streaming, APIs
- MLOps, CI/CD, DataOps (SHIP-HATS)
Practical notes
- This position is a 2-year fixed term contract.