Posted 4 days ago
[Contract] Analyst - Principal Analyst (Data Engineering Branch)NYP Nanyang Polytechnic
[Contract] Analyst - Principal Analyst (Data Engineering Branch)
EMA HQOn-siteFull-time
AI Summary
Designs, builds and operates secure, scalable data pipelines and platforms (data lakes, warehouses, lakehouses) for energy-sector regulatory, operational and analytics needs. Implements data quality controls, optimises performance and supports production workflows.
About this role
[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.
Skills
Apache SparkAWSCI/CDData GovernanceData LakesData LineageData ModellingData WarehousingETL/ELTJavaKafkaLakehouse ArchitectureMetadata ManagementMicrosoft AzurePySparkPythonScalaSQLVersion Control
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