The 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.

● 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

● Expert in cloud-native data services and architectures (e.g., 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.

● Ability to navigate complex enterprise landscapes and influence decision-making at executive levels.

● Proactively address technical debt, scalability bottlenecks, and architectural weaknesses to ensure data architecture evolves with business needs.

1 Job im Bereich Data Pipeline Optimization auf den Philippinen

Data Architect