[LTA-TRO] DATA ENGINEER, TRAFFIC & ROAD IT
The role involves designing, building, and scaling data infrastructure on AWS to support traffic and road analytics, including end‑to‑end ETL pipelines and CI/CD automation. The engineer will also enforce data quality, resolve production issues, and maintain comprehensive documentation such as data dictionaries and operational manuals.
Skills required
About this role
[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.
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