Director, Commercial Data Products

GSK•Philadelphia, PA

18h•Hybrid

About The Position

GSK is seeking a Director, Commercial Data Products to own and manage enterprise data products in the Commercial Activity and Customer & Account domains, including products such as Customer Interactions, Sales & Performance, and Customer 360. These products support commercial decisions and enable people and AI to access consistent, reliable information. The role establishes and maintains product vision, scope, data models, roadmaps, service levels, definitions, documentation, versioning, and adoption. This is a hands-on product-owner role that partners with engineering, analytics, commercial and field operations, technology, master data, and governance teams. The Director determines what is built and to what standard, leads contractors supporting the domains, and promotes high engineering standards through practices such as version control, peer review, automated testing, CI/CD, and documentation. Business functions retain ownership of the meaning of metrics and rules; this role encodes, versions, and certifies definitions supplied by named business owners. The role also owns key source relationships, coordinates with source stewards, and uses certified Customer Master data as a foundation for customer products. It manages product changes through advance notice, versioned releases, parallel runs, and mapping documentation. The Director acts as the domain authority for consuming teams and reports on product health, including SLA attainment, source onboarding and change timing, data integrity, adoption, and business impact. The position follows a hybrid working model, with flexibility to work remotely and onsite.

Requirements

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 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 a product roadmap, including gathering and prioritizing requirements, negotiating scope, making delivery commitments with clear 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 data 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 with 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 pharmaceutical data privacy requirements, including permitted-use and consent considerations.

Responsibilities

Own enterprise data products in the Commercial Activity and Customer & Account domains, including product vision, scope, SLAs, versioning, certification standards, and adoption; retire previous data products as appropriate.
Own the product roadmap by gathering and prioritizing stakeholder requirements, negotiating scope and trade-offs, and making delivery commitments against published capacity.
Represent the domains in demand review meetings and publish roadmaps, backlogs, and release notes.
Own conceptual, logical, and physical data models, designing for reuse and addressing effective dating, 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, set priorities and definitions of done, and ensure alignment with enterprise platform standards.
Champion and apply 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 without direct reporting authority.
Own key source relationships, such as syndicated sales and CRM data, with source data stewards; write contents-and-format specifications for sources and provide requirements for identity rules, hierarchies, and affiliations.
Consume certified Customer Master data as the foundation for Customer 360 products.
Encode, version, and certify business definitions and rules provided by named business owners; do not define metric meaning or certify without a named owner.
Certify products as AI-ready by clearing permitted use, documenting semantics, completing lineage, and maintaining catalog entries and documentation that enable self-service by teams and AI agents.
Manage product changes with advance consumer notice, versioned releases, parallel-run periods, and mapping documentation.
Serve 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.