[Contract] Analyst - Principal Analyst (Data Engineering Branch)

Public Service Division; Singapore; On-site; SGD 90,000 - 130,000; Full time

Job summary

Public Service Division in Singapore is seeking a data engineer to design, build and operate secure, scalable data platforms and pipelines supporting regulatory, operational, analytics and AI needs. You will transform diverse energy-sector data into trusted data products to improve availability, quality and insight.

The role covers batch and near-real-time pipelines, cloud and on-prem environments, data lakes and warehouses, ETL/ELT components, data governance and cost control, with

Qualifications

• Degree in Computer Science/Information Systems/Engineering or equivalent practical experience.
• Hands-on data engineering experience; internships/projects may count for entry level.
• Strong proficiency in SQL and at least one general-purpose programming language (Python/Java/Scala).
• Understanding of ETL/ELT design, data modelling, relational and non-relational databases, data warehousing, data lakes or lakehouse.
• Experience with data services on AWS or Microsoft Azure; advantageous.
• Knowledge of distributed data processing or streaming tech (Spark, PySpark, Kafka) is advantageous.
• Knowledge of data quality, metadata, lineage, access control, privacy and governance.
• Strong analytical and problem-solving skills; good written and verbal communication.

Responsibilities

• Design, build, test, deploy and maintain robust data pipelines ingesting 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 layers.
• Develop reusable ETL/ELT components, data models and transformation logic.
• Implement automated data validation, monitoring, lineage and alerting for data products.
• Optimise pipeline performance, storage, compute, and query efficiency with cost controls.
• Apply software engineering practices: version control, code reviews, CI/CD, tests, and documentation.
• Monitor production data workflows, troubleshoot failures and perform root-cause analysis for reliability.
• Collaborate with business users, system owners, analysts, data scientists and agencies to translate data requirements.
• Contribute to EMA’s data engineering standards and reusable patterns.

Skills

SQL

Python

Java

Scala

ETL/ELT

Data modelling

Data warehousing

AWS

Azure

Spark

Education

BSc/BE in Computer Science / Information Systems / Engineering

Tools

Apache Spark

Kafka

PySpark

Job description

[What the role is]

You will design, build and operate 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, you will transform diverse energy-sector data into trusted, reusable data products that improve data availability, quality and time to insight.

[What you will be working on]

The key responsibilities of the officer include:

• Design, develop, test, deploy and maintain robust batch and near-real-time data pipelines that ingest and integrate 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 accordance with enterprise architecture, security and governance standards.
• Develop reusable ETL/ELT components, data models and transformation logic using SQL and programming languages such as Python, Java or Scala.
• Implement automated data validation, reconciliation, monitoring, lineage and alerting controls to ensure the accuracy, completeness, freshness and reliability of data products.
• Optimise pipeline performance, storage, compute utilisation and query efficiency, while maintaining appropriate service levels and cost controls.
• Apply sound software engineering practices, including version control, code reviews, automated testing, CI/CD, technical documentation and configuration management.
• Monitor production data workflows, troubleshoot failures, perform root-cause analysis and implement sustainable improvements to platform reliability and maintainability.
• Work with business users, system owners, architects, analysts, data scientists, government agencies and industry partners to translate data requirements into secure, scalable and maintainable engineering solutions.
• Contribute to technical standards, reusable engineering patterns and continuous improvement of EMA’s data engineering capabilities.

[What we are looking for]

• Degree in Computer Science, Information Systems, Engineering or a related technical discipline, or equivalent practical experience.
• Hands-on experience in data engineering, data integration, data platform development or a related field. Fresh graduates with relevant internships, projects or technical portfolios may be considered for the entry-level position.
• Strong proficiency in SQL and at least one general-purpose programming language, preferably Python, Java or Scala.
• Sound understanding of ETL/ELT design, data modelling, relational and non-relational databases, data warehousing, data lakes or lakehouse architectures.
• Experience with data services on AWS or Microsoft Azure, such as object storage, serverless compute, orchestration, data integration, distributed processing and analytical databases, will be advantageous.
• Knowledge of distributed data processing or streaming technologies, such as Apache Spark, PySpark or Kafka, will be advantageous.
• Knowledge of data quality, metadata management, lineage, access control, privacy and data governance principles.
• Strong analytical and problem-solving skills, with the ability to diagnose complex data issues and develop pragmatic, sustainable solutions.
• Good written and verbal communication skills, with the ability to collaborate effectively across technical and business teams.
• A committed team player with a strong interest in public service and in shaping Singapore’s energy future.