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As a Principal Analyst, Data Integration, you will own the end-to-end process of evaluating, scoping, and onboarding new data sources into H1's platform.
This is a senior IC role at the intersection of data, engineering, and product — the connective tissue between raw data acquisition and what ultimately ships to clients.
You will work across Data & Research, Engineering, and Product to define what a new source is, how it maps to H1's schemas, what it can realistically deliver, and what it can't.
You will also work directly with client-facing teams to gather requirements before integration decisions are made, translating commercial needs into data specs and data constraints back into product expectations.
You will: - 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
As a Principal Analyst, Data Integration, you will own the end-to-end process of evaluating, scoping, and onboarding new data sources into H1's platform.
This is a senior IC role at the intersection of data, engineering, and product — the connective tissue between raw data acquisition and what ultimately ships to clients.
You will work across Data & Research, Engineering, and Product to define what a new source is, how it maps to H1's schemas, what it can realistically deliver, and what it can't.
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You will also work directly with client-facing teams to gather requirements before integration decisions are made, translating commercial needs into data specs and data constraints back into product expectations.
You will: - 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
AI-powered healthcare data platform helping life sciences, payers, providers, and patients identify and engage doctors.
Visit company websiteJobs and hiring trendsUSD 145000-170000 yearly
Full-time
Senior Level
Remote
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