AI Architect, Finance
We are the platform turning browsing into shopping. We connect 200 million shoppers with deals they love while boosting local sales for hundreds of top retailers and brands. We help…
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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
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About the companyH1Creating a healthier future worldwide by unlocking and democratizing global access to connected insights for all.
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