Job Description
The Data Strategy Leader will lead the development and execution of enterprise data strategy across priority data domains, ensuring data initiatives are directly aligned to enterprise priorities, measurable business outcomes, compliance expectations, and emerging AI needs. This leader will translate business goals into actionable data strategies, roadmaps, priorities, and value realization plans that improve data quality, interoperability, accessibility, reuse, and trust across the enterprise.
This role will serve as a strategic partner across business, technology, governance, stewardship, knowledge management, and solution delivery teams to define how enterprise data domains, data products, authoritative sources, and operating models should evolve to support scalable data and AI outcomes. The broader remit emphasizes aligning enterprise data domains, establishing authoritative sources, elevating literacy and governance, and accelerating data and AI outcomes through transparent catalogs, reusable components, and outcome-linked KPIs.
Key Responsibilities
Enterprise Data Strategy & Roadmap
Translate enterprise and divisional priorities into a measurable data strategy, including clear objectives, roadmaps, value drivers, KPIs, and execution priorities.
Align data initiatives with enterprise priorities and outcomes, ensuring investments in data capabilities are tied to measurable business, operational, compliance, and AI-enableable value.
Prioritize high-impact data use cases and convert business goals into analyses, roadmap decisions, and value realization plans.
Data Domains, Data Products & Authoritative Sources
Collaborate with Information Architecture to define clear enterprise data domains, sub-domains, data products, and accountable ownership structures.
Partner with data domain leads and stakeholders to define data requirements, current/near/future state needs, product roadmaps, onboarding priorities, data quality rules, governance expectations, and access-control requirements.
Standards, Quality, Interoperability & Lineage
Set expectations and strategic direction for data quality, interoperability, lineage, and reuse across enterprise data initiatives.
Ensure data strategy informs governance design, stewardship delivery, knowledge management, and product/architecture strategy across the end-to-end CDAO operating model.
Partner with data governance, stewardship, privacy, compliance, and knowledge management teams to ensure data strategies are trusted, compliant, and scalable.
Data & AI Enablement
Ensure responsible, compliant use of data and AI by embedding strategy, standards, source-of-truth clarity, provenance, quality, and governance expectations into data initiatives.
Support enterprise efforts to make high-quality data easier to discover, share, and use across the enterprise, including for AI-ready knowledge products and assets.
Help prioritize use cases that accelerate data and AI outcomes while maintaining clarity, confidence, and compliance.
Vendor, Contract & Sourcing Strategy
Partner with the Contract/Vendor Management Lead to create or align vendor management strategy for strategic data assets, data services, and external data needs.
Provide strategic input into buy/build recommendations, vendor performance expectations, SLA management, compliance alignment, and ROI measurement.
Leadership & Stakeholder Engagement
Act as a trusted strategic advisor to enterprise, divisional, and domain stakeholders on data strategy priorities, opportunities, tradeoffs, and execution paths.
Drive alignment across data strategy, governance, stewardship, knowledge management, engineering, solution delivery, activation, and divisional teams.
Build and mature the Data Strategy capability, including ways of working, priorities, operating rhythm, deliverables, and measurable outcomes. The Data Strategy area is described as having zero current headcount with a planned team buildout and immediate hiring needs.
Required Minimum Qualifications
Bachelor’s degree in business, accounting, life sciences, or related fieldrequired; advanced degree in business, sciences, or related discipline preferred.
Minimum of 10 years of relevant experience, including experience in commercial roles or enterprise business environments.
Significant experience leading enterprise data strategy, data governance, data management, data domains, data products, or related enterprise data transformation work.
Demonstrated ability to translate business strategy into measurable data roadmaps, KPIs, value realization plans, and execution priorities.
Strong understanding of data quality, metadata, lineage, interoperability, authoritative sources, data ownership, stewardship, governance, privacy, compliance, and AI-readiness principles.
AI awareness or practical experience applying AI-related governance principles, including responsible use, data readiness, risk management, and compliance considerations.
Experience working across federated business and technology environments, including collaboration with domain teams, product teams, engineering teams, governance teams, and senior stakeholders.
Ability to influence across organizational boundaries and drive alignment among business, technology, compliance, and data teams.
Strong executive communication skills, with the ability to simplify complex data strategy concepts into clear decisions, priorities, and business outcomes.
Preferred Qualifications
Experience in regulated industries such as life sciences, healthcare, pharmaceuticals, financial services, or other compliance-driven environments.
Experience with enterprise data domains such as Customer, Product, Reference Data, Real-World Data, IT Data, Manufacturing, Supply Chain, Commercial, Medical Affairs, or Corporate/GSF data. The remit identifies these as part of the enterprise domain enablement landscape.
Familiarity with data governance platforms, enterprise catalogs, semantic models, data quality frameworks, MDM/reference data, and AI/GenAI enablement patterns.
Experience developing operating models, maturity models, business cases, value scorecards, or data product strategies.
Experience assessing buy/build decisions, vendor strategies, data sourcing models, and ROI for data investments.
Ability to connect enterprise data priorities to measurable impact, including improved data quality, accessibility, reuse, interoperability, lineage, compliance, AI-readiness, and stakeholder trust.
Required Skills:
Business Analysis, Business Strategies, Data Governance, Data Quality, Data Science, Demand Management, Enterprise Data, Executive Communications, Innovation, Key Performance Indicators (KPI), Knowledge Management, Manufacturing, Product Roadmap, Requirements Management, Sourcing and Procurement, Stakeholder Engagement, Stakeholder Relationship Management, Standards Compliance, Stewardship, Strategic Planning
Preferred Skills:
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