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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in data product management, including ownership of data products, roadmap management, and stakeholder engagement. Proficient in data modeling, cloud data platforms, and ensuring data integrity and compliance in regulated industries.
Highest-signal resume keywords
Data Product ManagementData ModelingSQLDatabricksData Engineering
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Data EngineeringData ArchitectureDimensional ModelingEffective-DatingAutomated TestingCI/CDGitPythonSparkDbt
Soft Skills
CommunicationInfluencingFacilitationLeadership
Tools & Technologies
DatabricksSnowflakeAzureErwin Data ModelerUnity Catalog
Industry Keywords
Commercial Pharma DataHCP/HCO AffiliationsSyndicated Sales DataCustomer 360Healthcare Data Privacy
Tech Stack
Tools & technologiesAzureCloudPythonSnowflakeSparkSQLUnity
About the role
Key responsibilities & impact- Own key enterprise data products in the Commercial Activity and Customer & Account domains
- Set product vision, scope, SLAs, versioning, certification standards, and drive adoption while retiring previous data products
- Own the product roadmap by gathering and prioritizing stakeholder requirements, negotiating scope and trade-offs, and setting delivery commitments
- Represent the domains in demand review meetings and publish roadmaps, backlogs, and release notes
- Own conceptual, logical, and physical data models for the products
- Design for reuse, effective-dating, data restatements, HCP/HCO hierarchies and affiliations, and consistent keys across masters and products
- Partner with the matrixed engineering team building and maintaining products on Databricks
- Champion Git-based version control, peer-reviewed pull requests, automated tests, CI/CD, and everything-as-code
- Review designs and code and contribute hands-on when needed
- Lead contractors supporting the domains, setting priorities and quality standards and ensuring knowledge retention
- Influence engineering and stewardship partners without direct reporting lines
- Own source relationships feeding the domains, including syndicated sales data and CRM data
- Write contents-and-format specifications for each source and provide requirements for identity rules, hierarchies, and affiliations
- Encode, version, and certify business definitions and rules supplied by named business owners
- Certify products as AI-ready with permitted use cleared, documented semantics, and complete lineage
- Maintain catalog entries and documentation for self-service by teams and AI agents
- Manage changes through advance notice, versioned releases, parallel-run periods, and mapping documentation
- Act as domain authority for consuming teams
- Report on product health, including SLA attainment, source availability, data integrity, adoption, and impact
- Explain complex data topics in business terms and influence senior stakeholders
Requirements
What you’ll need- Bachelor’s degree in Computer Science, Information Systems, Data Science, or a related field, or an equivalent combination of education and experience
- 10+ years of experience in data engineering, data product management, data architecture, or data management
- Data engineering experience, including Git and strong coding best practices — branching, pull requests, peer code review, automated testing, and CI/CD
- Strong SQL and experience with dbt and/or Python or Spark
- Experience in conceptual, logical, and physical data model design for analytical or enterprise data platforms
- Experience with dimensional modeling, effective-dating, and handling historical restatement
- Experience managing a product roadmap, gathering and prioritizing stakeholder requirements, negotiating scope, making commitments with clear delivery timelines, and delivering against them
- Experience leading contractor, contingent, and matrixed teams
- Experience owning data products or data assets end to end, with defined SLAs, versioning, documentation, and measured adoption
- Experience with commercial pharma data and ecosystems, including CRM interactions, syndicated sales and market data, HCP and account data, and field execution use cases
- Experience with modern cloud data platforms such as Databricks, Snowflake, and Azure
- Experience with a lakehouse layering approach (raw, enriched, curated)
- Preferred: Master’s or other advanced degree in a related field
- Preferred: Strong facilitation, communication, and influencing skills
- Preferred: Significant experience in a regulated industry such as healthcare, pharmaceuticals, or life sciences
- Preferred: Experience with Databricks and Unity Catalog, and dbt as the authoring layer for transformation logic
- Preferred: Experience with Veeva CRM data, IQVIA or other syndicated data, and HCP/HCO affiliations and hierarchies
- Preferred: Experience with Customer 360 or similar multi-source customer data products, including consuming a mastered customer domain
- Preferred: Hands-on experience with Erwin Data Modeler or comparable data modeling tools
- Preferred: Experience defining schema contracts, data quality tests, and observability for production pipelines
- Preferred: Strong experience with semantic layers, metric governance, data catalogs, and lineage tools
- Preferred: Experience preparing data products for AI and agent consumption
- Preferred: Experience leading or supporting cloud platform migrations, including dual-running periods
- Preferred: Working knowledge of Agile delivery and healthcare and pharma data privacy requirements, including permitted-use and consent considerations
Benefits
Comp & perks- Comprehensive benefits program for US employees (details provided in GSK US Benefits Summary)
- Hybrid working model with flexibility to work remotely and onsite
- Equal opportunity employment
- Reasonable accommodation or other assistance to apply
