The Lead Data Architect will focus on designing secure and scalable healthcare data architectures using cloud platforms while ensuring alignment with clinical and operational goals. He/she will be involved in implementing governance frameworks, maintaining regulatory compliance, and enabling interoperability through industry standards like HL7 and FHIR. He/she will optimize data
pipelines, maintain data quality, and collaborating with stakeholders to meet evolving healthcare data needs.
Key Functions:
- Design and implement scalable, secure, and resilient healthcare data architectures using cloud platforms such as GCP, AWS, or Azure.
- Establish and uphold enterprise-level data architecture principles, standards, and governance frameworks to support both clinical and operational needs.
- Create comprehensive models for structured, semi-structured, and unstructured data, ensuring consistency with the MVP's Key Data Elements (KDEs).
- Work closely with stakeholders to gather data requirements, develop strategic data approaches, and convert business objectives into technical solutions.
- Develop and enforce healthcare data governance policies to ensure compliance with HIPAA and other applicable regulations (e.g., GDPR), safeguarding data privacy and security across the entire data lifecycle.
- Oversee the integration of new data sources and use cases, ensuring alignment with existing data architecture and governance protocols.
- Document complete data lineage and incorporate metadata management and data quality standards into architectural designs.
- Promote interoperability among healthcare systems (e.g., EHRs, LIS, PACS) by aligning data architecture with industry frameworks such as HL7, FHIR, and DICOM.
- Identify and recommend suitable technologies for data storage, integration, transformation, and visualization based on business needs and compliance requirements.
- Guide Data Engineers in building data pipelines and optimizing them for both batch and real-time processing.
- Continuously assess and improve technology stacks for data infrastructure.
- Implement performance monitoring systems to ensure the efficiency and reliability of data operations.
- Performs other tasks and duties as may be assigned/ delegated by the superiors.
Qualifications:
- 10 years of experience, with 3-5 years specifically focused on data warehouses, databases, and other data-related fields.
- BigQuery, Dataproc, Dataflow, Glue, Redshift).
- Strong understanding of relational and NoSQL database technologies (e.g., PostgreSQL, MongoDB).
- Proficient in data modelling techniques, including conceptual, logical, and physical data models.
- Experience designing and implementing data lakes, data warehouses, and lakehouse solutions.
- Deep understanding of data governance frameworks and tools (e.g., Collibra, Alation, Informatica).
- Strong understanding of data architecture frameworks and design patterns.
- Experience embedding data lineage, data quality, and master data management into architectural design.
- Expert in data modeling techniques (dimensional, relational, etc.) and schema design.
- Strong understanding of data security principles and best practices in a cloud environment.
- Familiarity with handling PHI/PII data in a compliant and secure manner. Strong leadership, communication, and stakeholder management skills to drive alignment across business and technical teams.
