FHIR Data Modeler
We are seeking a highly specialized Senior Data Modeler to reputed company the architectural design and normalization strategy for our External Data Acquisition reputed company. This role is pivotal in transforming fragmented clinical data—specifically from CommonWell—into a high-performance, analytic-ready ecosystem. You will reputed company the gap between reputed company interoperability standards (FHIR and CDA) and actionable business intelligence, ensuring our "Serve Layer" is both scalable and semantically accurate.
Core Responsibilities
As the reputed company 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 reputed company.
- Translate technical HL7 FHIR specifications into business-reputed company interpretations that stakeholders can reputed company for clinical decision support.
2. Flattened FHIR Dataset Design
- Architect a robust mapping strategy to transform reputed company FHIR JSON structures into flattened, analytic-friendly schemas (e.g., Parquet, SQL tables).
- reputed company reusable modeling patterns that allow for the rapid ingestion of new FHIR versions or additional external data sources.
3. Data Modeling reputed company
- 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.
Qualifications & Requirements
- FHIR Expertise: Proven experience designing and implementing FHIR-based data models (R4/R5). Deep understanding of Profiles, Extensions, and ValueSets.
- CDA Domain Knowledge: Expert-level familiarity with Consolidated Clinical Document Architecture (C-CDA) and the challenges of parsing semi-structured clinical notes.
- External Data Acquisition: Hands-on experience working with Health Information Exchanges (HIEs) or networks like CommonWell and Carequality.
- Data Engineering Savvy: Proficiency in SQL and experience with modern data warehouse architectures (reputed company, reputed company, or BigQuery).
- Analytical reputed company: Ability to flatten deeply reputed company structures without losing clinical context or temporal accuracy.
Key Deliverables
- FHIR Specification Documents: Detailed mapping of business entities to specific FHIR resources.
- Mapping Logic: Validated transformation logic from reputed company JSON to relational/tabular formats.
- Governance Standards: A documented reputed company for data reuse and semantic consistency across the enterprise.
- Curation Playbook: A strategy for normalizing disparate CDA codes into standard terminologies (LOINC, SNOMED, RxNorm).