Senior Data Engineer, Traffic & Road IT Analytics
Builds and scales the data infrastructure behind Singapore's Land Transport Authority's traffic and road analytics, owning the full data lifecycle: designing ETL/ELT pipelines on AWS, automating CI/CD via SHIP-HATS, enforcing data quality, and maintaining documentation and post-deployment system health across agile squads.
- Compensation
- Not disclosed
- Location
- Singapore, Singapore
- Work setup
- Not specified
- Seniority
- Senior
- Employment
- Not specified
- Experience
- 3+ years
- Category
- Data engineering
- Posted
Skills
Must have
- Knowledge in Computer Science, Data Engineering, Software Engineering, or a related field
- At least 3 years of experience in data engineering, data analytics, or a related discipline
- Foundational understanding of data engineering concepts including data modelling and ETL/ELT pipelines
- Proficiency in SQL
- Basic working knowledge of at least one programming language such as Python
- Familiarity with at least one cloud platform such as AWS or Azure
- Strong communication and collaboration skills across the project lifecycle from feasibility studies to post-deployment support
- Proactive and analytical problem-solving with 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) SENIOR/ EXECUTIVE DATA ENGINEER, TRAFFIC & ROAD IT
**(What the role is)
**(LTA-TRO) SENIOR/ EXECUTIVE 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)
- Knowledge in Computer Science, Data Engineering, Software Engineering, or a related field, with at least 3 years of experience in data engineering, data analytics, or a related discipline.
- The following skills are mandatory: a foundational understanding of data engineering concepts including data modelling and ETL/ELT pipelines; proficiency in SQL and basic working knowledge of at least one programming language such as Python; and familiarity with at least one cloud platform such as AWS or Azure.
- The following skills are advantageous: 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.
- Strong communication and collaboration skills, with the ability to contribute across the project lifecycle from data feasibility studies to post-deployment support, and a proactive and analytical approach to problem-solving with 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.