Lead, Business Data Strategy

Responsibilities

• Drive IDP strategy and operationalization - Lead the transition from legacy data environments (e.g., Snowflake) to IDP, ensuring alignment to business priorities, clean intake, and disciplined execution tied to USPD outcomes.
• Own data product adoption and effectiveness - Ensure IDP data products are usable, trusted, and embedded in day-to-day decision-making across operational and business teams.
• Translate business needs into prioritized work - Partner with operational and business leaders to shape use cases, define requirements, and prioritize work based on business impact.
• Orchestrate cross-functional delivery - Coordinate across data engineering, analytics, and AI teams to deliver integrated solutions-holding teams accountable to outcomes, timelines, and quality.
• Advance business-led AI enablement - Partner with cross-functional teams to identify and scale AI opportunities that improve decision-making and operational efficiency across the business unit.
• Track and communicate business impact / Ensure data governance alignment - Define success measures and communicate how IDP and AI capabilities improve decision-making and efficiency.
• Partner with data governance teams to ensure data products meet standards for quality, access, privacy, and regulatory requirements.
• Other duties as assigned
• Minimum Requirement
• Degree or equivalent and typically requires 10+ years of relevant experience. Less years required if has relevant Master's or Doctorate qualifications.
• Education
• Bachelor's degree in Business, Information Systems, Data Science, or related field.
• Critical Skills
• 10+ years of experience across business, operations, data, or analytics in a large, complex organization
• Additional Skills
• Strong ability to translate between business and technical teams
• Working knowledge of modern data platforms (e.g., Snowflake, Databricks) without needing to build
• Experience driving adoption of data and analytics solutions
• Operational mindset (intake, prioritization, governance, scaling)
• Clear, executive-level communication focused on outcomes and decisions
• Ability to lead through influence across multiple teams
• Environment
• This role is a hybrid position . The selected candidate is expected to work on-site at our Las Colinas office a minimum of two (2) days per week , with the remaining days worked remotely. Specific in-office days may be designated based on team needs and business priorities.
• Working Conditions
• Traditional office or hybrid environment, depending on location. Some travel required for cross-site collaboration and customer/partner engagements.
• McKesson complies with all applicable U.S. immigration laws and regulations. The Company does not provide employer support or sponsorship for any immigration related employment benefit for this role.
• If you will require McKesson to provide immigration support or sponsorship now or in the future, you should not apply for this position
• Travel Requirements
• Occasional travel (varies by business needs) for cross-functional planning sessions.
• Physical Requirements
• Sedentary work with prolonged periods of sitting and computer use.

Benefits

Additional Information

McKesson is an impact-driven, Fortune 10 company that touches virtually every aspect of healthcare. We are known for delivering insights, products, and services that make quality care more accessible and affordable. Here, we focus on the health, happiness, and well-being of you and those we serve - we care. What you do at McKesson matters. We foster a culture where you can grow, make an impact, and are empowered to bring new ideas. Together, we thrive as we shape the future of health for patients, our communities, and our people. If you want to be part of tomorrow's health today, we want to hear from you. Role Summary A lead individual contributor role within US Pharmaceutical Distribution focused on advancing the Intelligent Data Platform (IDP) from build to scale. This role is accountable for driving platform adoption, operationalizing data products, and translating business needs into prioritized, high-impact data and AI capabilities. The role partners across the business unit, data engineering, and AI teams to ensure the platform delivers measurable business value-not just technical outputs.

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