Manager, Data Strategy (Enterprise Finance)

We’re building a world of health around every individual — shaping a more connected, convenient and compassionate health experience. At CVS Health®, you’ll be surrounded by passionate colleagues who care deeply, innovate with purpose, hold ourselves accountable and prioritize safety and quality in everything we do. Join us and be part of something bigger – helping to simplify health care one person, one family and one community at a time.

Position Summary

At CVS Health, we’re building a world of health around every individual — shaping a more connected, convenient and compassionate health experience.

The Manager, Data Strategy will help Enterprise Finance treat data as a strategic asset by defining, coordinating, and advancing a coherent data strategy and data product approach that enables analytics, reporting, and AI use cases at enterprise scale. This role sits within the Data & AI Strategy & Governance portfolio and partners across Finance and Technology to translate business priorities into a clear strategy, roadmap, and measurable outcomes.

This is a cross-functional role operating at the intersection of business stakeholders and data/technology teams, focused on improving the usability and value of shared data assets through clear strategy, prioritization, and adoption.

Key Responsibilities:

Data Strategy & Roadmap

• Develop and maintain a data strategy roadmap that aligns data initiatives with business goals, accounts for dependencies, and evolves through continuous iteration as needs change.
• Partner with stakeholders to identify high‑value opportunities where improved data availability, consistency, or productization will accelerate decision‑making and reduce friction for teams.
• Define success measures and track progress using meaningful metrics (e.g., adoption, usability, reliability, and business outcomes where applicable).

Data Product Strategy (Defining “What we’re building” and “How it’s used”)

• Help define and communicate clear data product concepts, including intended consumers, usage patterns, and lifecycle expectations (e.g., documentation, reliability, discoverability, and interoperability).
• Translate business needs into actionable product requirements and collaborate with engineering/ architecture partners to shape feasible delivery plans.
• Drive internal adoption by ensuring data products are understandable and usable for intended consumers (training, enablement materials, feedback loops).  

Cross‑Functional Alignment & Execution Enablement

• Serve as a connector between Finance stakeholders and technical teams to align on priorities, sequencing, and tradeoffs while maintaining clarity on scope and expected value.
• Coordinate work across related functions (e.g., data governance, data engineering, analytics enablement) to reduce duplication and improve consistency in shared data assets and definitions.
• Contribute to portfolio-level governance by supporting decision forums with clear options, risks, impacts, and recommended paths forward.

Standards, Quality, and “Fitness for Use” (in partnership with Governance)

• Partner with Data Governance and other control stakeholders to ensure data strategy and data products align with enterprise expectations for security, compliance, and appropriate use.
• Incorporate pragmatic expectations for data quality, documentation, and stewardship so that products remain trusted and support repeatable decision processes.

Required Qualifications

• 5+ years of experience in data strategy, data product management, analytics strategy, program management, or a related role in a complex enterprise environment.  
• Demonstrated experience creating roadmaps and translating business needs into structured initiatives, requirements, and execution plans.
• Strong stakeholder management skills; ability to work across business and technical teams to drive alignment and outcomes.
• Analytical and structured problem-solving skills, including comfort with ambiguity and the ability to define “what good looks like” for data initiatives.

Preferred Qualifications

• Experience with “data as a product” practices, including defining internal data consumers, adoption goals, and ongoing lifecycle ownership.
• Familiarity with enterprise data management concepts (e.g., metadata/ catalog, quality expectations, standardized definitions) and how they enable scalable analytics.
• Finance domain familiarity (e.g., planning, reporting, performance management) and comfort operating in environments with heightened control expectations.

Education

• Bache