Product Manager, Data Harmonization

Datavant is the data collaboration platform trusted for healthcare. Guided by our mission to make the worlds health data secure accessible and actionable we provide critical data solutions for organizations across the healthcare ecosystem - including providers health plans researchers and life sciences companies. From fulfilling a single patients request for their medical records to powering the AI revolution in healthcare Datavanters are building the future of how data is connected and used to improve health.

By joining Datavant today youre stepping onto a driven and highly collaborative team that is passionate about creating transformative change in healthcare.

Datavant is seeking a versatile technically fluent and commercially minded Product Manager to own Data Harmonization within our Life Sciences business. This role sits on the Data Utility team which develops privacy remediation and harmonization capabilities that make health data more usable for research and analytics.

At Datavant data harmonization means transforming disparate real-world datasets into standardized quality-validated privacy compliant analytics-ready assets. The workflow includes profiling source data; mapping schemas and clinical concepts; normalizing formats units and vocabularies; validating outputs; managing exceptions; and producing traceable datasets aligned to a common or customer-defined data model and meeting the privacy requirements to be HIPAA de-ID. These capabilities must integrate cleanly with Datavants ingestion privacy expert determination and downstream analytics workflows.

This is a zero-to-one product strategy and execution role not simply a feature-delivery role. You will begin by defining the end-to-end harmonization workflow with customers and our Delivery team including where software can automate work and where expert judgment remains necessary. You will then determine which capabilities Datavant should build buy or deliver through partners leading structured vendor evaluations and proofs of concept.

As the strategy matures you will turn repeatable delivery work into scalable software reusable mapping assets and a commercially viable product offering. You will partner closely with Engineering Data Science Delivery Privacy Platform and Go-to-Market teams and work directly with customers data engineering informatics analytics and research teams.

Success in this role will be measured by reducing the time and effort required to move from source data to analytics-ready outputs; increasing reuse of mappings and transformation rules; improving data quality lineage and reproducibility; reducing manual delivery effort and rework; and driving customer adoption.

• Own the product strategy and roadmap for data harmonization. Define the target users priority use cases product boundaries business case and phased path from service-supported workflows to scalable product capabilities.
• Define and own the end-to-end workflow. Map the process from source-data intake profiling and quality assessment through schema and semantic mapping transformation validation privacy and remediation and final analytics-ready delivery.
• Clarify how harmonization interacts with privacy and remediation. Define the sequencing data contracts and controls required so that privacy transformations preserve mapping integrity analytical utility and source-to-output traceability.
• Lead build buy and partner decisions. Establish evaluation criteria assess vendors run proofs of concept using representative datasets and make defensible recommendations.
• Define the technical requirements and build reusable assets. Work with Engineering to spec the full pipeline: intake quality checks mapping transformation validation and delivery (file API or data platform) with full traceability. Productize (or implement via a partner) the mapping templates transformation rules and validation logic into governed reusable components versioned and auditable rather than artifacts rebuilt for every engagement. This could also include integration with external or internal systems.
• Design for real-world operational complexity. Define requirements for human review and exception management schema drift incremental data refreshes failed transformations quality thresholds monitoring and ongoing support.
• Engage customers directly. Understand customers source data target models use-cases and delivery constraints. Translate those needs into clear product requirements without allowing one-off requests to overwhelm the scalable product strategy.
• Partner with Data Science and Delivery to productize services. Identify the most repetitive and costly parts of current delivery workflows establish baselines for manual effort and rework validate proposed automation and measure the product impact.
• Shape the commercial offering with GTM. Help define packaging implementation models pricing inputs positioning and sales enablement.
• Lead execution as the product matures. Serve as the Agile Product Owner by prioritizing the backlog writing requirements and acceptance scenarios managing dependencies and partnering with Engineering through discovery delivery launch adoption and iteration.
• Define and track product performance. Establish metrics to track offering performance such as time to analytics-ready data percentage of mappings and rules reused automated mapping coverage and customer adoption.

• 5 years of product management or technical product ownership experience preferably with data platforms data integration developer tools enterprise workflows or analytics products.
• Experience owning a complex product from discovery and strategy through delivery launch adoption and ongoing improvement.
• Demonstrated experience making build-versus-buy-or-partner decisions including vendor evaluation technical due diligence proof-of-concept design business-case development and total-cost-of-ownership analysis.
• Strong grounding in data integration and ETL/ELT concepts including pipelines schema mapping transformation APIs metadata lineage validation and batch or incremental processing.
• Enough technical fluency to review data dictionaries source-to-target mapping specifications SQL API documentation transformation logic and data-quality results with engineers and data scientists. You are not expected to be a production engineer but you must be comfortable working at this level of detail.
• Experience translating complex expert-led or services-heavy workflows into repeatable product capabilities and internal or customer-facing software.
• Familiarity with one or more health data models and standards such as OMOP CDISC/SDTM or HL7 FHIR and an understanding that common data models research submission standards and exchange standards serve different purposes.
• Strong analytical and product judgment including the ability to define success metrics test assumptions evaluate tradeoffs and make decisions with incomplete information.
• Experience working directly with enterprise customers and translating differing customer requirements into a coherent scalable product strategy.
• Strong written and verbal communication skills with the ability to explain complex technical decisions keep open questions visible and align stakeholders across Product Engineering Data Science Delivery Privacy and GTM.
• Highly organized and comfortable managing ambiguity dependencies and competing priorities while driving decisions and maintaining momentum.
• Experience delivering enterprise-grade software and operating within Agile product-development teams.
• Passion for improving healthcare and making health data more usable trustworthy and valuable.

• Experience with real-world data and evidence including claims electronic health records laboratory pharmacy registry or clinical research data.
• Hands-on experience implementing or working with OMOP or another healthcare common data model.
• Familiarity with clinical and administrative vocabularies such as ICD-10 SNOMED CT LOINC RxNorm CPT or NDC.
• Experience with data-quality frameworks source-to-target mapping governance terminology management or metadata and lineage platforms.
• Experience with cloud data platforms and technologies such as Snowflake Databricks AWS SQL or Python.
• Exposure to healthcare privacy de-identification expert determination regulated research environments or GxP-related workflows.
• Experience partnering deeply with data science informatics epidemiology biostatistics or data-delivery teams.

To ensure the safety of patients and staff many of our clients require post-offer health screenings and proof and/or completion of various vaccinations such as the flu shot Tdap COVID-19 etc. Any requests to be exempted from these requirements will be reviewed by Datavant Human Resources and determined on a case-by-case basis. Depending on the state in which you will be working exemptions may be available on the basis of disability medical contraindications to the vaccine or any of its components pregnancy or pregnancy-related medical conditions and/or religion.

This job is not eligible for employment sponsorship.

Datavant is committed to a work environment free from job discrimination. We are proud to be an Equal Employment Opportunity employer and all qualified applicants will receive consideration for employment without regard to race color sex sexual orientation gender identity religion national origin disability veteran status or other legally protected learn more about our commitment please review our EEO Commitment Statement here. Know Your Rights explore the resources available through the EEOC for more information regarding your legal rights and addition Datavant does not and will not discharge or in any other manner discriminate against employees or applicants because they have inquired about discussed or disclosed their own pay.

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