Director, Commercial Data Products

GSK•Philadelphia, PA

2d•Hybrid

About The Position

The Director, Commercial Data Products owns key enterprise data products in GSK’s Commercial Activity and Customer & Account domains, such as Customer Interactions, Sales & Performance, and Customer 360. These products are designed to help people and AI access consistent, reliable information for commercial decisions. The role establishes product vision, data models, roadmaps, service-level agreements, versioning, documentation, and certification standards, and drives adoption while managing the retirement of previous products. This is a hands-on product owner position that partners closely with engineering, analytics, commercial and field operations, technology, master data, and data governance teams. The Director determines product scope and delivery priorities, leads a team of contractors, and champions engineering quality through version-controlled, peer-reviewed, tested, and documented code. The role is accountable for product reliability, published definitions, catalog documentation, and adoption, while business owners retain responsibility for defining the meaning of metrics and rules. The position also manages source relationships and data models, ensures responsible and well-documented changes, and certifies products as AI-ready when permitted use is cleared, semantics are documented, and lineage is complete. It reports on product health, including SLA attainment, data integrity, adoption, and impact, and explains complex data topics to business stakeholders.

Requirements

Bachelor’s degree in Computer Science, Information Systems, Data Science, or a related field, or an equivalent combination of education and experience.
10 or more years of experience in data engineering, data product management, data architecture, or data management.
Data engineering experience, including Git and strong coding practices such as branching, pull requests, peer code review, automated testing, and CI/CD.
Strong SQL and experience with dbt and/or Python or Spark.
Experience designing conceptual, logical, and physical data models for analytical or enterprise data platforms, including dimensional modeling, effective-dating, and historical restatement.
Experience managing product roadmaps, prioritizing stakeholder requirements, negotiating scope, making commitments with clear delivery timelines, and delivering against them.
Experience leading contractor, contingent, and matrixed teams, setting direction and quality standards, and delivering through people who do not report directly to you.
Experience owning data products or assets end to end, with defined SLAs, versioning, documentation, and measured adoption.
Experience with commercial pharmaceutical data and ecosystems, such as 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, and a lakehouse layering approach (raw, enriched, curated).

Nice To Haves

Master’s or other advanced degree in a related field.
Strong facilitation, communication, and influencing skills, including negotiating with senior stakeholders and presenting complex data topics to large audiences.
Significant experience in a regulated industry such as healthcare, pharmaceuticals, or life sciences.
Experience with Databricks and Unity Catalog, and dbt as the authoring layer for transformation logic.
Experience with Veeva CRM data, IQVIA or other syndicated data, and HCP/HCO affiliations and hierarchies.
Experience with Customer 360 or similar multi-source customer data products, including consuming a mastered customer domain such as Reltio.
Hands-on experience with Erwin Data Modeler or comparable data modeling tools.
Experience defining schema contracts, data quality tests, and observability for production pipelines.
Strong experience with semantic layers, metric governance, data catalogs, and lineage tools, and preparing data products for AI and agent consumption.
Experience leading or supporting cloud platform migrations, including dual-running periods.
Working knowledge of Agile delivery and healthcare and pharma data privacy requirements, including permitted-use and consent considerations.

Responsibilities

Own enterprise data products in the Commercial Activity and Customer & Account domains, setting product vision, scope, SLAs, versioning, certification standards, and adoption plans, and retiring previous products.
Own the product roadmap by gathering and prioritizing stakeholder requirements, negotiating scope and trade-offs, making delivery commitments against published capacity, and publishing roadmaps, backlogs, and release notes.
Own conceptual, logical, and physical data models, designing for reuse and addressing effective-dating, data restatements, HCP/HCO hierarchies and affiliations, and consistent keys.
Partner with the matrixed engineering team to determine what is built, in what order, and to what definition of done, following enterprise platform standards.
Champion engineering best practices, including 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 by setting priorities, quality standards, and expectations and ensuring knowledge is documented and retained.
Influence engineering and stewardship partners who contribute to the products without direct reporting lines.
Own key source relationships, such as syndicated sales and CRM data, alongside source data stewards; write contents-and-format specifications for each source.
Use the certified Customer Master as the foundation for 360 products and provide requirements for identity rules, hierarchies, and affiliations.
Encode, version, and certify business definitions and rules supplied by named business owners; do not define metric meaning or certify without a named owner.
Certify products as AI-ready, with permitted use cleared, semantics documented, lineage complete, and sufficient catalog entries and documentation for self-service by teams and AI agents.
Manage product changes with advance consumer notice, versioned releases, parallel-run periods, and mapping documentation when definitions or structures change.
Act as domain authority for consuming teams and report on product health, including SLA attainment, time to availability for new sources and upstream changes, internal data integrity, adoption, and data impact.
Explain complex data topics in business terms and influence senior stakeholders using data.