Associate Director, Pharma Commercial Data Management

We are seeking an Associate Director, Pharma Commercial Data Management to provide strategic and operational leadership for the development, stewardship, and delivery of scalable, analytics-ready data products supporting commercial analytics and decision-making.

This role is responsible for translating business needs into functional data requirements, partnering closely with IT and analytics teams, and prioritizing and driving delivery of high-quality, governed data products through DevOps and vendor teams.

Key Responsibilities

Own and Manage Requirements for Data Products

• Understand business use cases and translate them into clear, actionable functional requirements for data models.

• Collaborate with Intelligence Product Owners and Analytics teams to document business rules and ensure alignment with analytical needs.

• Serve as the primary point of accountability to prioritize data product requirements based on business value, analytics impact, and delivery feasibility.

• Provide ongoing direction and clarification to DevOps and vendor teams to ensure requirements are implemented as intended.

Data Modeling

• Provide direction and guidance on the design and evolution of scalable data architecture supporting commercial analytics use cases.

• Define logical data models and oversee physical data models that support reusability, performance, and governance.

• Ensure data models are analytics-ready, scalable, and aligned to defined success metrics.

Partner with IT team

• Collaborate closely with Gilead IT to execute new build projects and enhancements.

• Oversee and guide DevOps teams to ensure timely and high-quality delivery of data solutions.

• Align technical design with business requirements and ensure architectural consistency.

• Ensure operational excellence in data ingestion, transformation, and delivery processes.

• Build and maintain robust, scalable, and automated data pipelines across internal and external sources.

• Prioritize, plan, mitigate tech & business risks and manage outcomes of DevOps teams delivering data ingestion, transformation, and analytics-ready datasets.

Own and Manage Kite Master Data Management (MDM)

• Manage HCP (Healthcare Professional) , HCO and Payer MDM systems to ensure accurate, complete, and unified customer profiles.

• Ensure MDM processes and outputs align with Kite’s business requirements and downstream analytics needs.

• Promote and remove barriers to adoption of MDM across all domains and function and actively.

Data Stewardship, Governance & Compliance

• Ensure data products are clean, timely, compliant, and analytics-ready through strong stewardship, governance, and quality practices.

• Drive data quality monitoring, alerting, and remediation processes in partnership with IT and vendors.

• Define data quality success metrics and ensure remediation activities are appropriately prioritized.

• Manage vendor SLAs and ensure adherence to data quality, governance, and compliance standards.

• Oversee practical governance practices including metadata management, access control, and data lineage.

• Ensure compliance with internal policies and external regulations (e.g., GDPR, CCPA).

Data Onboarding & Data Products

• Adopt enterprise mindset for data products.·

• Ensure clear specifications and Functional Impact Assessments (FIAs) for onboarding new data sources.

• Establish, monitor, and enforce SLAs with external vendors to ensure timely and accurate data delivery.

• Lead onboarding of new data sources, stabilize them to a steady state, and manage ongoing cadence with data partners.

• Own data products end-to-end, from onboarding through steady-state operations, ensuring reliability, relevance, and sustained business value.

• Continuously evaluate existing data products to optimize cost, quality, and usability.

Self-Service & AI.

• Enable self-service for commercial business functions by increasing access to trusted, well-documented data products and insights.

• Work with leadership to shape the roadmap for AI based transformation of data governance and data product management and own the execution.

• Develop and plan and execution strategy to evolve the data products and enable GenAI ready data backbone

• 'Leverage AI tools to simplify on-demand access to trusted data and insights while maintaining governance and quality standards.

Basic Qualifications

PhD in Data Management, Computer Science, Information Systems, or a related field and 5 + years of related experience

OR

Masters degree in Data Management, Computer Science, Information Systems, or a related field and 8 + years of related experience

OR

Bachelor’s degree in Data Management, Computer Science, Information Systems, or a related field and 10+ years of related experience

Preferred Qualifications

• 8–10+ years of experience in commercial data management, data modeling, and data operations, preferably in life sciences or pharmaceutical organizations

• 6+ years working with pharmaceutical commercial data, including HCP, account, and engagement data

• Deep experience in data governance, including MDM, data stewardship, and data quality management, with accountability for operational outcomes

• Experience building, operating, and evolving cloud-based data warehouses and/or data lakes supporting analytics-ready data products

• Strong hands-on experience with modern data platforms and analytics platforms with the ability to guide architectural and delivery decisions. AWS, Databricks, Tableau experience preferred

• AI enthusiast with hands-on experience developing AIdriven solutions for data management, analytics, and/or reporting

• Proven experience leading complex cross-functional data initiatives and directing delivery through DevOps teams and vendor partners.

• Strong communication and stakeholder management skills, with demonstrated ability to influence priorities and translate technical concepts into business and analytics outcomes.

• Demonstrated ability to build durable partnerships across business, IT, analytics, and external partners.

• Ability to present data products, delivery status, risks, and roadmap tradeoffs to senior and diverse stakeholder audiences.