Staff Clinical Informatics Data Architect

Verily Health is a data platform and technology company purpose-built to power AI-enabled precision health solutions that accelerate research and improve care for individuals and communities. Uniquely positioned at the intersection of technology, data science, and healthcare, Verily transforms multimodal health data into insights, models, and actions that make healthcare more personalized, predictive, and precise.

Responsibilities

As a technical leader, oversee the plan, design, and execution of data modeling, normalization, and transformation activities. These efforts will support the development of an advanced healthcare data architecture that aligns with organizational goals and adheres to informatics standards.

Lead the design of healthcare data modeling and mapping of source data to FHIR, OMOP and STDM. This will involve data normalization, enrichment, and deduplication to enhance data quality and completeness. To ensure accurate representation of clinical concepts, source data will need to be standardized to terminologies and ontologies like SNOMED, LOINC, RxNorm, and others.

Oversee the integration strategy for ingestion of multi-sourced healthcare data focused on ingesting multi-sourced healthcare data received through standard interoperability exchange protocols, such as FHIR, HL7, and X12 ED.

Architect and oversee the design of robust data pipelines that can handle large volumes of data efficiently and reliably, enabling timely analysis and intervention in time-sensitive situations.

Champion data quality initiatives, establishing rigorous standards and processes to ensure the reliability and accuracy of data.

Foster collaboration between technical and non-technical teams, translating complex technical concepts into actionable insight.

Drive the exploration and adoption of emerging technologies and methodologies, such as machine learning or artificial intelligence.

Design documents that effectively communicate data architecture, normalization principles, and harmonization techniques to technical and non-technical stakeholders across the organization.

Apply expertise to solve complex, high-impact data-related issues, ensuring timely resolution and minimizing disruptions to critical operations.