[LTA-TRO] DATA ENGINEER, TRAFFIC & ROAD IT

Land Transport Authority (LTA) Singapore; Singapore; On-site; SGD 70,000 - 110,000; Full time

Job summary

Land Transport Authority (LTA) Singapore is seeking a Data Engineer to own, build and scale the data infrastructure powering analytics and applications. You will bridge hands-on pipeline development with cloud architecture and collaborate across squads.

Responsibilities include implementing robust ETL/ELT processes, maintaining data quality checks, and documenting data dictionaries and operations. Knowledge in data modelling, SQL, Python, and cloud platforms (AWS/Azure) is essential.

Qualifications

• Foundational knowledge of data engineering concepts including data modelling and ETL/ELT pipelines.
• Proficiency in SQL and at least one programming language (Python).
• Interest or coursework in cloud platforms such as AWS or Azure.

Responsibilities

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

Skills

Data modelling

ETL/ELT pipelines

SQL

Python

Cloud platforms (AWS/Azure)

Tools

Apache Airflow

dbt

Delta Lake

Power BI

Tableau

Job description

[What the role is]

[LTA-TRO] DATA ENGINEER, TRAFFIC & ROAD IT

[What the role is]

[LTA-TRO] DATA ENGINEER, TRAFFIC & ROAD IT

[What you will be working on]

We are looking for a Data Engineer to own, build, and scale the data infrastructure powering our next-generation analytics and applications. In this role, you will bridge hands-on pipeline development with AWS cloud architecture, working across agile squads to champion data engineering best practices and modern 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 maintaining post-deployment system health. Beyond writing clean code, you will ensure long-term operational excellence by embedding strict data quality checks, resolving production issues, and maintaining comprehensive technical documentation like data dictionaries and operational manuals.

Education:

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

Mandatory Skills:

Foundational understanding of data engineering concepts including data modelling and ETL/ELT pipelines (academic or project-based exposure is acceptable); proficiency in SQL; basic working knowledge of at least one programming language such as Python; and demonstrated interest or coursework in cloud platforms such as AWS or Azure.

Advantageous Skills:

Exposure to workflow orchestration tools such as Apache Airflow; familiarity with modern data stack tools such as dbt or Delta Lake; exposure to CI/CD practices including SHIP-HATS; familiarity with data governance principles and IM8 compliance standards; and experience with data visualisation tools such as Power BI or Tableau.

Soft Skills & Attributes:

Strong communication and collaboration skills; ability to contribute across the project lifecycle from data feasibility studies to post-deployment support; a proactive and analytical approach to problem-solving; and a strong sense of ownership over data quality and pipeline performance.

As part of the shortlisting process for the role, you may be required to complete a medical declaration and / or undergo further assessment.