Data Engineer: Cloud Pipelines & Analytics

Public Service Division; Singapore; On-site; SGD 75,000 - 110,000; Full time

Job summary

Public Service Division is seeking a Data Engineer to own, build, and scale our data infrastructure powering analytics and applications. You will bridge hands-on pipeline development with AWS cloud architecture, working across agile squads to champion data engineering best practices and CI/CD automation through SHIP-HATS.

You will drive the entire data lifecycle—from assessing upfront data feasibility and aligning performance specifications with stakeholders, to building robust ETL processes and

Qualifications

• Must have foundational knowledge of data engineering concepts including data modelling and ETL/ELT pipelines; SQL proficiency; basic Python; exposure to cloud platforms such as AWS or Azure.
• Experience or coursework in cloud platforms (AWS or Azure) and data governance principles is a plus.
• Familiarity with CI/CD practices including SHIP-HATS is advantageous.

Responsibilities

• Own, build, and scale the data infrastructure powering analytics and applications.
• Bridge hands-on pipeline development with AWS cloud architecture.
• Champion data engineering best practices and CI/CD automation.
• Maintain data quality checks and operational documentation.

Skills

SQL

Python

AWS

Azure

Data modelling

ETL/ELT pipelines

CI/CD practices

SHIP-HATS

Education

Knowledge in Computer Science, Data Engineering, Software Engineering, Information Systems, or related field

Tools

Airflow

dbt

Delta Lake

Power BI

Tableau

Job description

Public Service Division is seeking a Data Engineer to own, build, and scale our data infrastructure powering analytics and applications. You will bridge hands-on pipeline development with AWS cloud architecture, working across agile squads to champion data engineering best practices and CI/CD automation through SHIP-HATS.

You will drive the entire data lifecycle—from assessing upfront data feasibility and aligning performance specifications with stakeholders, to building robust ETL processes and