Senior Data Engineer (Databricks, Power BI)
Salary: $6,500 – $8,500 per month
About the role
You will be part of a high-performing and multi-disciplinary research division that conducts a range of research initiatives that impacts policy and operations in Singapore's social service sector. The Senior Data Engineer will mentor data engineers to build and maintain robust infrastructure and systems across digital ecosystem. The team will be instrumental in supporting the development of data pipelines and infrastructure that ensure clean, accurate, and timely data is available for business analytics, decision-making, and AI applications.
Key responsibilities
- Guide and plan data engineering processes for digital systems
- Lead technical discussions with the data engineering team and stakeholders to shape the future of digital products
- Lead and advise agency on data engineering strategy, architecture, and implementation aligned with the Digital Government Blueprint (DGB2.0)
- Provide technical leadership across multiple product teams by establishing data architecture standards and developer operations best practices
- Mentor and train the data engineering team
- Assist in designing and developing data pipelines and architectures to collect, process, harmonize and store data from various source systems
- Support the building of data pipelines that integrate data from multiple platforms and services
- Help maintain data lakes and database infrastructure to support analytical, reporting, and AI workloads
- Implement data validation, cleansing, and normalisation processes to ensure data quality and integrity
- Monitor data pipelines and systems to identify potential issues and performance bottlenecks
About you
- Bachelor's Degree in Computer Science, Data Science, Engineering, Information Technology, or related technical field
- 5+ years of experience in data engineering, cloud infrastructure, platform engineering or related technical roles
- Proficiency in at least one programming language such as Python, Java, or Scala for data processing and scripting
- SQL knowledge essential
- Advanced knowledge of data modelling and schema design principles
- Familiarity with data integration and ETL (Extract, Transform, Load) concepts and processes
- Basic experience with version control systems such as Git
- Basic familiarity with cloud platforms, preferably AWS services such as S3, EC2, and RDS
- Experience with any cloud platform (AWS, Azure, or GCP)
- Experience with Databricks and implementing batch/real-time data pipelines