Energy Data Engineer — Real-Time Analytics & Data Lakes

Energy Market Authority (EMA); Singapore; On-site; SGD 70,000 - 110,000; Full time

Job summary

Energy Market Authority (EMA) in Singapore seeks a data-focused professional to architect Singapore's energy data ecosystem. You will leverage data modelling, cloud platforms and distributed computing (Spark) to build data lakes and real-time analytics, aligning with EMA's strategic goals.

You will design end-to-end data processes, develop ETL and data governance, and collaborate with government partners to explore AI/ML technologies in the energy sector.

Qualifications

• Education in CS, DS, Stats, Economics with quantitative content.
• Experience in data engineering, data analytics or ML projects; strong data/cloud knowledge.
• Strong foundation in data modelling and data architecture for optimized analytics.
• Experience with AWS/Azure data services or similar cloud platforms preferred.
• Familiarity with Gen AI tech like LLMs advantageous.

Responsibilities

• Design, build, deploy, manage end-to-end data processes and data products.
• Manage development, testing and maintenance of enterprise data systems per Agile.
• Develop scalable ETL processes for ingesting data from diverse sources (on-prem and cloud).
• Maintain data quality, governance and reporting for management stakeholders.
• Collaborate with business users and partners to explore AI/ML data tech and solutions.

Skills

Data modelling

Data engineering

Statistical analysis

Cloud technologies

AI/ML techniques

Programming languages

Problem solving

Communication

Education

Computer Science

Data Science

Statistics

Economics

Tools

Python

R

SAS

Java

Scala

Job description

Energy Market Authority (EMA) in Singapore seeks a data-focused professional to architect Singapore's energy data ecosystem. You will leverage data modelling, cloud platforms and distributed computing (Spark) to build data lakes and real-time analytics, aligning with EMA's strategic goals.

You will design end-to-end data processes, develop ETL and data governance, and collaborate with government partners to explore AI/ML technologies in the energy sector.