Responsibilities
- Lead structured evaluation of new data sources from scratch, assessing schema, coverage, freshness, legal constraints, and fit against product needs before engineering begins.
- Own field mapping from source to bronze, silver, and 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, serving as the authoritative voice on source capabilities and limitations before product commitments.
- Shepherd each source end-to-end from scoping through QA, entity matching, and 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, owning onboarding rather than ongoing maintenance.
- Produce and maintain documentation that others actually use, including scoping assessments, field mapping specs, and post-mortems.
Requirements
- 8–12+ years in data-focused roles at healthcare data companies, pharma or biotech data vendors, health IT firms, or equivalent.
- Demonstrated end-to-end ownership of data integrations built from scratch, including scoping, field mapping, QA, and handoff, with documentation to show for it.
- Healthcare or life sciences domain context required, with ability to ramp on new datasets and source types each quarter without needing deep subject matter expertise upfront.
- Analytical fluency to assess data quality, with hands-on experience using tools such as VBA, R, or SPSS; SQL is 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.
- Exceptional written communication, with documentation that is legible, maintained, and actually used.
Nice to Have
- AWS infrastructure familiarity (Athena, S3, Glue) at a query and inspection level preferred.
- Comfort working in Jira or Monday in a ticket-based workflow.
Compensation
Full suite of health insurance options, in addition to generous paid time off
Work Arrangement
Flexible work hours and the opportunity to work from anywhere
Other
- Full suite of health insurance options, in addition to generous paid time off
- Pre-planned company-wide wellness holidays
- Retirement options
- Health and charitable donation stipends
- Impactful Business Resource Groups
- Flexible work hours and the opportunity to work from anywhere
- The opportunity to work with leading biotech and life sciences companies in an innovative industry with a mission to improve healthcare around the globe
