[LTA-TRO] DATA ENGINEER, TRAFFIC & ROAD IT
Data Engineer at Singapore's Land Transport Authority building and scaling AWS-based data infrastructure for traffic and road analytics: developing ETL/ELT pipelines, embedding data quality checks, and maintaining CI/CD via SHIP-HATS. Entry-level friendly; core stack is SQL, Python, AWS, with Airflow, dbt and Power BI as pluses.
- Compensation
- Not disclosed
- Location
- Singapore, Singapore
- Work setup
- Not specified
- Seniority
- Not specified
- Employment
- Not specified
- Experience
- Not specified
- Category
- Data engineering
- Posted
Skills
Must have
- Knowledge in Computer Science, Data Engineering, Software Engineering, Information Systems, or a related field
- Foundational understanding of data engineering concepts including data modelling and ETL/ELT pipelines (academic or project-based exposure acceptable)
- Proficiency in SQL
- Basic working knowledge of at least one programming language such as Python
- Demonstrated interest or coursework in cloud platforms such as AWS or Azure
- Strong communication and collaboration skills
- Proactive and analytical approach to problem-solving
- Strong sense of ownership over data quality and pipeline performance
Nice to have
- 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
- Experience with data visualisation tools such as Power BI or Tableau
Full description
(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.
(What we are looking for)
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.