Healthcare Data Architect

Essential Functions: Build and maintain reusable Epic Cosmos, SlicerDicer, DSVM, SQL, Cogito, Clarity, and Caboodle query assets for research, education, quality improvement, real world evidence, and precision health projects. Develop validated SQL-based data marts, research-ready analytic datasets, dashboards, notebooks, and reusable analytic templates in approved secure analytics environments. Translate faculty, student, clinical, genomic, operational, and research questions into computable cohorts, data specifications, phenotype definitions, and reproducible analytic workflows. Partner with Cook Children’s Epic analysts, clinical informaticists, statisticians, privacy/security teams, and UTA researchers to support compliant healthcare data workflows. Support project intake, feasibility assessment, prioritization, documentation, portfolio tracking, and contributions to abstracts, manuscripts, grants, reports, presentations, and leadership deliverables. Create and maintain data dictionaries, query examples, validation protocols, user guides, training materials, and technical documentation for healthcare informatics users. Design and implement data-quality and validation workflows addressing coding variation, missingness, duplicate records, vocabulary mapping, unit harmonization, site heterogeneity, and phenotype drift. Performs other duties as assigned.

Required Qualifications: Doctoral degree or clinical doctorate with research training, such as a PhD, DrPH, MD, DO, PharmD, DNP, and three (3) years of experience conducting healthcare data research, including statistical analysis, study design, and work with clinical or real-world healthcare data; OR eleven (11) years of an equivalent combination of education and experience.

Preferred Qualifications: Experience using Epic systems, Cosmos, or similar healthcare data platforms; working in clinical informatics, epidemiology, or real-world evidence research, and contributing to scientific writing and publication.