Principal Analyst, Data Integration

H1 provides a platform designed to improve access to healthcare information and support better patient outcomes through data and AI technology. The company is seeking a Principal Analyst, Data Integration to own the end-to-end evaluation, scoping, onboarding, and quality assurance of new data sources into H1's platform while working across Data & Research, Engineering, Product, and client-facing teams.

Responsibilities:

• Lead structured evaluation of new data sources from scratch — assessing schema, coverage, freshness, legal constraints, and fit against H1's product needs before any engineering work begins
• Own field mapping from source to H1's bronze/silver/gold layers, producing data dictionaries, entity definitions, and structural guidance for downstream teams
• Partner with engineering and Data Lake to define ingestion requirements, entity resolution rules, and refresh cadences for new sources
• Gather requirements from client-facing teams and translate them into integration specifications; serve as the authoritative voice on what a new source can and cannot deliver before product commitments are made
• Shepherd each source end-to-end: scoping → QA → entity matching → product launch, including product QA and communicating source capabilities and limitations to product and enablement partners
• Work with the Insights team to develop new taxonomies and QA mechanisms for novel data types
• Define acceptance criteria and lead QA validation including field-level fill rates, count comparisons, and cycle-over-cycle anomaly detection
• Investigate and resolve data quality issues post-integration, coordinating with DART and engineering as needed
• Hand off to the maintaining team with complete mapping documentation; you own onboarding, not ongoing maintenance
• Produce and maintain documentation other people actually use — across scoping assessments, field mapping specs, and post-mortems

Requirements:

• • 8–12+ years in data-focused roles at healthcare data companies, pharma/biotech data vendors, health IT firms, or equivalent
• • Demonstrated end-to-end ownership of data integrations built from scratch — scoping, field mapping, QA, and handoff — with documentation to show for it
• • Healthcare or life sciences domain context required; ability to ramp on new datasets and source types each quarter without needing deep subject matter expertise upfront
• • Analytical fluency to assess data quality; hands-on experience with tools such as VBA, R, or SPSS; SQL a plus but not a primary requirement
• • Familiarity with data lake architectures (bronze/silver/gold or equivalent) and how raw data moves through normalization and entity resolution to a product-ready state
• • Experience gathering requirements from client-facing stakeholders and translating them into data or product specifications
• • Experience at a B2B data company where you understood how external clients consumed your data and where client retention drove decisions
• • Comfort working in Jira or Monday in a ticket-based workflow
• • Exceptional written communication — your documentation is legible, maintained, and actually used
• • AWS infrastructure familiarity (Athena, S3, Glue) at a query and inspection level preferred