Data Engineer, AI Clinical Data Platform (Contract)

About the role

This is a contract position within the Singapore Medical Foundation AI Model Programme (SIMFONI), a national initiative driving AI adoption across Singapore's public healthcare system. As a Data Engineer, you will design, build and maintain the clinical data platform powering AI-enabled Clinical Decision Support Systems on the SIMFONI Conductor platform. You will work closely with software engineers, AI engineers, clinicians, Synapxe and healthcare stakeholders to deliver reliable, secure and reusable data capabilities.

Key responsibilities

• Design, develop and maintain clinical data pipelines, transformation workflows and data assets for the SIMFONI Conductor platform.
• Build and manage canonical data models, data mappings and integration frameworks across clinical systems.
• Implement data quality controls, validation, lineage tracking and governance to ensure data integrity and compliance.
• Monitor, troubleshoot and optimise data pipelines and database performance.
• Collaborate with clinicians, engineers, product teams and partners on system integrations and platform delivery.
• Support testing, deployment, production operations, release management and continuous improvement.
• Maintain technical documentation, data dictionaries, operational procedures and release records.

Required profile

• Bachelor's degree in Computer Science, Data Engineering, Information Systems, Data Science, Health Informatics or a related discipline.
• 3-5+ years of experience in data engineering, database engineering, analytics engineering or data platform development.
• Experience with healthcare, clinical, EHR or other regulated datasets, and familiarity with healthcare data governance and interoperability requirements.
• Experience supporting cloud-based data platforms on AWS, Azure or GCP.
• Professional certifications in Data Engineering, Database Technologies, AWS, Azure or related cloud platforms.

Required skills

• Strong SQL and Python, with ETL/ELT pipeline building and optimisation.
• PostgreSQL, dbt, Apache Airflow or similar data engineering and orchestration tools.
• Data modelling, data governance, data quality management and database optimisation.
• Linux, Git and modern software development practices.