Data Engineer (MSF) New Government Technology Agency | InfoComm, Technology, New Media Communications Easy Apply A day ago
Data Engineer at Singapore's GovTech (Singpass) who designs, builds, and maintains data pipelines and analytics infrastructure — spanning batch and real-time processing, data modelling (star/snowflake schemas, SCD), and platform optimisation — using Python, SQL, Databricks, and AWS. 2-year fixed-term contract in Singapore.
- Compensation
- Not disclosed
- Location
- Singapore, Singapore
- Work setup
- Not specified
- Seniority
- Not specified
- Employment
- Contract
- Experience
- 3+ years
- Category
- Data engineering
- Posted
Skills
Must have
- Minimum 3-5 years of experience in data engineering, data analytics, or related technical field
- Demonstrated experience designing and implementing data pipelines and analytics solutions
- Strong knowledge of data modelling: star schema, snowflake schema, wide table designs
- Proficient in Slowly Changing Dimension (SCD) patterns and their use cases
- Understanding of Data Lake, Data Warehouse, Data Lakehouse, and Data Mesh architecture patterns
- Proficient in Python with data manipulation libraries (pandas, numpy), pipeline frameworks, and API development
- Strong SQL skills for querying, transformation, and database management
- Solid foundation in data ingestion, transformation, quality assurance, and pipeline orchestration
- Knowledge of data governance, lineage tracking, and metadata management
- Strong analytical and problem-solving skills
- Excellent communication skills to collaborate with technical and non-technical stakeholders
Nice to have
- Knowledge of Databricks and AWS cloud services
- Familiarity with infrastructure-as-code and DevOps practices for data platforms
Full description
The Government Technology Agency (GovTech) is the lead agency driving Singapore’s Smart Nation initiatives and public sector digital transformation. As the Centre of Excellence for Infocomm Technology and Smart Systems (ICT & SS), GovTech develops the Singapore Government’s capabilities in Data Science & Artificial Intelligence, Application Development, Smart City Technology, Digital Infrastructure, and Cybersecurity.
AtGovTech, we offer you a purposeful career to make lives better. We empower our people to master their craft through continuous and robust learning and development opportunities all year round. OurGovTechiesembody our Agile,Boldand Collaborative values to deliver impactful solutions.
GovTech aims to transform the delivery of Government digital services by taking an \"outside-in\" view, putting citizens and businesses at the heart of everything we do. Play a part in Singapore’s vision to build a Smart Nation and embark on your meaningful journey to build tech for public good.
Join us to advance our mission and shape your future with us today!
Learn more aboutGovTechat tech.gov.sg
(What you will be working on)
As a Data Engineer, you will be responsible for designing, developing, and maintaining robust data infrastructure that enables analytics and insights across the organisation. You will work closely with business stakeholders, data analysts, and other technical teams to deliver scalable data solutions that support data-driven decision making. Your job scope includes (but not limited to) the following:
- Requirements Analysis and Solution Design: Collaborate with business users, data analysts, and stakeholders to elicit and document requirements for analytics use cases. Translate business requirements into technical specifications and design optimal data architecture solutions that align with organisational data strategy and governance frameworks.
- Data Pipeline Architecture and Design: Design end-to-end data pipelines from various source systems to different layers within the data analytics platform, including bronze (raw), silver (technical), and gold (business) layers. Ensure pipeline designs follow best practices for scalability, reliability, and maintainability whilst adhering to data governance and security requirements.
- Data Pipeline Development and Implementation: Develop, test, and deploy data pipelines using modern data engineering tools and frameworks. Implement data transformation logic, quality checks, and error handling mechanisms to ensure reliable data processing. Build automated workflows that can handle both batch and real-time data processing requirements.
- Data Infrastructure Maintenance and Optimisation: Monitor and maintain existing data pipelines to ensure optimal performance, reliability, and cost-effectiveness. Troubleshoot data quality issues, resolve pipeline failures, and implement performance improvements. Conduct regular reviews of data infrastructure to identify opportunities for enhancement and modernisation.