Senior/Executive Data Engineer - Transport AI Programme

About the role

The Land Transport Authority (LTA) is investing in AI capabilities to improve how Singapore's land transport network is sensed, managed and optimised. As a Data Engineer in the Transport AI Programme, you will design, build and maintain the data infrastructure and pipelines that let AI models and applications access high-quality, timely and trustworthy data. The role reports to the Transport AI Programme Deputy Director and works closely with AI software developers, the AI architect, infrastructure engineers and industry partners.

Key responsibilities

• Design, build and maintain scalable data pipelines that ingest, transform and serve structured and unstructured data from real-time streams and batch feeds.
• Develop and manage data models, data catalogues and feature stores for AI model training, evaluation and inference.
• Ensure data quality, consistency and lineage, with validation checks, monitoring and alerting.
• Implement data governance in line with Singapore Government data classification requirements, including access controls, masking, anonymisation and audit logging.
• Work with the AI Architect and Infrastructure Engineer to design performant, cost-efficient data infrastructure in LTA's cloud and hybrid environment.
• Collaborate with data scientists and AI developers to turn data requirements into production-grade data products.
• Support integration of external data sources from industry partners and contribute to shared data platforms and reusable data assets.
• Maintain data pipelines in production and support incident response.

Required profile

• Computer Science, Data Science, Business Analytics or related field, with at least 3-6 years of relevant experience; assessed on experience and may be considered at intermediate or senior level.
• Experience in regulated, government or critical infrastructure environments is a plus.
• Comfortable working in cross-functional teams and explaining technical concepts to non-technical stakeholders; inclined to work in an Agile environment.

Required skills

• Proficiency in Python and SQL.
• Data pipeline frameworks such as Apache Spark, Apache Kafka, dbt, Airflow or equivalent.
• Cloud data platforms (AWS Glue, Azure Data Factory, Google Dataflow, Databricks) and data warehousing or lakehouse architectures.
• Streaming data processing is a strong advantage; feature stores for ML/AI workloads are highly desirable.