Manager, Artifical Intelligence Office (Contract)
Overview
Join 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 (AI-CDSS) on the SIMFONI Conductor platform. You will develop scalable data pipelines, canonical clinical data models, and governed data services that enable high-quality data to be used by AI models, analytics solutions, and clinical applications across public healthcare institutions.
Working closely with software engineers, AI engineers, clinicians, Synapxe, and healthcare stakeholders, you will play a key role in delivering reliable, secure, and reusable data capabilities that support the operationalisation of AI solutions at scale.
Key Responsibilities
- Design, develop, and maintain clinical data pipelines, transformation workflows, and data assets supporting the SIMFONI Conductor platform.
- Build and manage canonical data models, data mappings, and integration frameworks across multiple clinical systems.
- Implement data quality controls, validation mechanisms, lineage tracking, and governance processes to ensure data integrity and compliance.
- Monitor, troubleshoot, and optimise data pipelines and database performance to maintain platform reliability and scalability.
- Collaborate with clinicians, engineers, product teams, Synapxe, and external partners to support system integrations and platform delivery.
- Support testing, deployment, production operations, release management, and continuous improvement initiatives.
- Maintain technical documentation, data dictionaries, operational procedures, and release records.
Requirements
- 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.
- Strong proficiency in SQL and Python with experience building and optimising ETL/ELT pipelines.
- Experience with PostgreSQL, dbt, Apache Airflow, or similar data engineering and workflow orchestration tools.
- Strong understanding of data modelling, data governance, data quality management, and database optimisation.
- Experience working with Linux environments, Git, and modern software development practices.
- Strong analytical, troubleshooting, and problem-solving skills.
- Excellent communication and stakeholder management skills.
- Experience working with healthcare, clinical, EHR, or other regulated datasets.
- 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.
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