Principal Analyst - Data Engineering (Contract)

About the role

The Principal Analyst in the Data Engineering Branch designs, builds and operates secure, scalable and reliable data platforms and pipelines that support EMA's regulatory, operational, analytics and artificial intelligence needs. Working across cloud and on-premises environments, the role turns diverse energy-sector data into trusted, reusable data products that improve data availability, quality and time to insight.

Key responsibilities

• Design, develop, test, deploy and maintain batch and near-real-time data pipelines that ingest structured, semi-structured and unstructured data from internal and external sources.
• Build and enhance cloud and on-premises data platforms, including data lakes, lakehouses, data warehouses and curated data layers, in line with enterprise architecture, security and governance standards.
• Develop reusable ETL/ELT components, data models and transformation logic using SQL and languages such as Python, Java or Scala.
• Implement automated data validation, reconciliation, monitoring, lineage and alerting controls.
• Optimise pipeline performance, storage, compute usage and query efficiency while keeping service levels and costs under control.
• Apply software engineering practices such as version control, code reviews, automated testing, CI/CD, technical documentation and configuration management.
• Monitor production workflows, troubleshoot failures, perform root-cause analysis and improve platform reliability.
• Work with business users, system owners, architects, analysts, data scientists, government agencies and industry partners to turn data requirements into secure, scalable solutions.
• Contribute to technical standards, reusable patterns and continuous improvement of EMA's data engineering capabilities.

Required profile

• Degree in Computer Science, Information Systems, Engineering or a related technical discipline, or equivalent practical experience.
• Hands-on experience in data engineering, data integration or data platform development; fresh graduates with relevant internships, projects or portfolios may be considered.
• Strong analytical and problem-solving skills, good written and verbal communication, and a commitment to public service and Singapore's energy future.

Required skills

• SQL and at least one general-purpose language, preferably Python, Java or Scala.
• ETL/ELT design, data modelling, relational and non-relational databases, data warehousing, data lakes or lakehouse architectures.
• Advantageous: AWS or Azure data services, Apache Spark, PySpark or Kafka, data quality, metadata management, lineage, access control and data governance.