We are seeking a highly specialized Senior Data Modeler to lead the architectural design and normalization strategy for our External Data Acquisition stream. This role is pivotal in transforming fragmented clinical data—specifically from CommonWell—into a high-performance, analytic-ready ecosystem. You will bridge the gap between complex interoperability standards (FHIR and CDA) and actionable business intelligence, ensuring our "Serve Layer" is both scalable and semantically accurate. Core Responsibilities As the lead architect for data acquisition, you will be responsible for the following key pillars: 1. FHIR Structure Design & Specification Execute resource-level decomposition of incoming clinical bundles (Patient, Observation, Encounter, etc.) to ensure data integrity. Translate technical HL7 FHIR specifications into business-aligned interpretations that stakeholders can leverage for clinical decision support. 2. Flattened FHIR Dataset Design Architect a robust mapping strategy to transform nested FHIR JSON structures into flattened, analytic-friendly schemas (e.g., Parquet, SQL tables). Develop reusable modeling patterns that allow for the rapid ingestion of new FHIR versions or additional external data sources. 3. Data Modeling Framework Establish and maintain a Serve Layer alignment strategy, ensuring that acquired external data integrates seamlessly with internal clinical records. Define and document standards for reuse across various clinical domains (Pharmacy, Lab, Claims) to minimize redundant engineering efforts. 4. CDA to FHIR Normalization Strategy Provide deep-dive CDA/FHIR mapping insights, specifically targeting the nuances of CommonWell document exchanges. Accelerate the curation and normalization of C-CDA documents into FHIR resources to ensure a longitudinal view of the patient record.
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Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed