Clinical Data Architect
J
JobgetherHealthcare data
Based in United StatesFull-TimeSenior
SalaryBase salary range of $119,500–$179,000, depending on location, experience, skills, education, and other job-related factors. Additional bonus and equity opportunities.
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Job Details
- Experience
- 5+ years of professional experience in healthcare data architecture, clinical informatics, or a related field within healthcare or life sciences.
- Required Skills
- PythonSQLdbt
Requirements
- Bachelor’s degree in Computer Science, Information Systems, or a related technical discipline.
- 5+ years of professional experience in healthcare data architecture, clinical informatics, or a related field within healthcare or life sciences.
- Strong experience with healthcare data models and interoperability standards, including OMOP, FHIR R4/R5, HL7 v2, CDA/CCD-A, or NCPDP.
- Advanced proficiency in Python and SQL.
- Hands-on experience integrating and transforming healthcare data.
- Demonstrated understanding of clinical data structures, healthcare terminology, interoperability, and data harmonization.
- Experience designing or implementing healthcare data architecture and integration solutions.
- Hands-on experience with dbt and Jupyter Notebooks is preferred.
- A Master’s degree, professional certification in Clinical Informatics, PharmD, or comparable clinical informatics experience is preferred.
- Strong analytical, organizational, and problem-solving skills, with attention to data quality and detail.
- Written and verbal communication skills to explain technical and clinical data concepts to stakeholders with varying levels of expertise.
- Ability to work independently and collaborate across multidisciplinary teams.
Responsibilities
- Architect FHIR-compliant clinical data models aligned with implementation guides, profiles, and internal standards.
- Design and operationalize strategies to harmonize and enrich clinical data from EHRs, health information exchanges, claims, and other sources.
- Develop and maintain scalable FHIR-to-OMOP transformation pipelines using dbt and SQL.
- Standardize healthcare data using SNOMED CT, LOINC, ICD-10, and RxNorm.
- Design and manage custom value sets for clinical and research requirements.
- Establish validation frameworks and algorithms to ensure data accuracy, consistency, completeness, and longitudinal integrity.
- Document data architecture and clinical informatics requirements for technical and non-technical stakeholders.
- Collaborate across teams to improve the usability, interoperability, and reliability of clinical data.
- Contribute to healthcare data architecture and integration practices as data needs and standards evolve.
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