PGS Data Governance Lead

The PGS Data Governance Lead reports directly to the VP, PGS Data, Analytics & AI Transformation and serves as a member of the team’s leadership team. This global senior leadership role is accountable for defining and executing PGS’s data governance strategy, ensuring critical data is trusted, controlled, and fit for purpose across master data, planning parameters, transactional data, and structured and unstructured data assets. 

The leader owns the end-to-end governance operating model, including policies, standards, stewardship expectations, quality rules, observability, anomaly actioning, and automated remediation across human and AI-enabled workflows. The role also drives metadata, lineage, and Collibra documentation to strengthen transparency, discoverability, and trust in enterprise data. 

Accountable for data trust, compliance, security, and risk-based prioritization, this role enables secure, governed access to data for AI, analytics, and enterprise large language model initiatives. By ensuring trusted, governed data is available, accurate, and secure, the leader positions PGS to scale AI-driven decision-making with confidence. 

Data Governance Strategy & Operating Model 

• Define and execute the PGS data governance strategy, roadmap, and value realization plan across master data, planning parameters, transactional data, and structured and unstructured data assets. 

• Own the governance operating model, including policies, standards, stewardship expectations, quality rules, observability, anomaly actioning, and automated remediation across human and AI-enabled workflows. 

Global Stewardship & Data Ownership 

• Establish, lead, and mature a global network of embedded data stewards and data owners, ensuring clear ownership, consistent accountability, and strong execution across governed data domains. 

• Coach stewards and owners to improve data accuracy, embed governance into day-to-day operations, and connect local stewardship activity to enterprise governance priorities. 

Governed Data Domain Accountability 

• Own governance accountability across core master data and Single-Entry domains, including Material, Plant, Vendor, Serialization, Location, Source & Destination, and Resource data. 

• Prioritize expansion into additional critical PGS datasets, including Quality, External Supply, and Procurement, based on business value, risk, readiness, and enterprise data priorities. 

Project Representation & Portfolio Enablement 

• Ensure governed data domains are appropriately represented in projects that rely on, create, modify, or consume critical data, bringing steward and owner expertise into project design, decision-making, and delivery. 

• Balance enterprise standards with divisional and functional needs, ensuring governance support is prioritized and resourced across the active portfolio. 

Data Quality, Automation & Workflow Innovation 

• Partner with Data Engineering, data stewards, and data owners to define data quality rules, detection algorithms, workflow requirements, and automation opportunities that improve accuracy and reduce manual effort at scale. 

• Lead testing, validation, formal acceptance, and continuous improvement of data quality outputs and outlier workflow capabilities to ensure issues are consistently routed, tracked, resolved, and prevented. 

Metadata, Lineage & Data Transparency 

• Drive metadata management, lineage, Collibra documentation, and data health practices so governed data assets are transparent, discoverable, trusted, and usable by business users, technical teams, and AI/analytics solutions. 

Compliance, Risk & Secure AI Enablement 

• Accountable for data trust, compliance, security, and risk-based prioritization across governed data assets, ensuring governance decisions protect Pfizer while enabling appropriate access and use. 

• Enable secure, governed access to data for AI, analytics, enterprise large language model initiatives, and data-driven decision-making across PGS in partnership with Digital and business leaders. 

Key Capabilities

• Leading Through Change: Demonstrated experience leading leaders and teams through complex change, including navigating ambiguity, influencing across stakeholders, and sustaining performance during transformation.
• Digital Literacy and AI Fluency: Strong digital literacy, including practical experience leveraging data, digital tools, and AI‑enabled solutions to drive innovation, efficiency, and better decision‑making.
• End‑to‑End Process Thinking: Proven ability to think and operate end‑to‑end, connecting strategy to execution across functions and anticipating downstream impacts to deliver integrated, enterprise‑level solutions.
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• Applicant must have a bachelor’s degree in Data Management, Information Systems, Computer Science, Business, Supply Chain, or a related field with at least 12 years of experience; OR a master’s degree with at least 10 years of experience; OR a PhD with at least 7 years of experience. 

• Demonstrated success building and leading enterprise-scale data governance, data management, data quality, master data management, analytics, compliance/risk, or related programs, including policy, stewardship, operating model, and senior-management accountability. 

• Proven leadership of business-critical teams and global stewardship or governance networks, including mentoring embedded stewards, building a high-performing culture, and enabling independent ownership across a large, matrixed organization. 

• Strong ability to partner with Data Engineering, Digital, and business stakeholders to translate data quality, governance, and business requirements into rules, algorithms, automated solutions, validation approaches, and production-ready capabilities. 

• Working knowledge of data governance, metadata, lineage, and data quality platforms and practices, with the ability to quickly learn new data domains and translate complex technical governance concepts into clear guidance for technical and non-technical stakeholders. 

• Demonstrated understanding of how trusted, governed data enables AI, analytics, enterprise decision-making, compliance, security, and risk-based data access in regulated or similarly complex environments. 

• Proven ability to operate in a highly matrixed, federated organization while balancing enterprise standards with divisional/functional autonomy. 

• Business-level fluency in English (written and verbal)  for effective global collaboration and executive communication. 

• Master’s degree or professional certification in Data Governance, Data Management, or a comparable recognized discipline, such as DAMA CDMP. 

• Strong AI, technical, and business acumen, with the ability to connect governance strategy to supply chain, manufacturing, enterprise priorities, analytics use cases, data architecture, automation, and platform capabilities. 

• Evidence of innovation, intellectual rigor, structured problem-solving, and sound judgment in managing trade-offs across competing data priorities and stakeholder needs. 

• Execution-focused change leader with a proven ability to move strategy through implementation, ongoing operation, sustainment, and continuous improvement in large, complex organizations. 

• Excellent communication, presentation, facilitation, collaboration, and influencing skills across data stewards, owners, technical teams, senior leaders, and executive stakeholders, including influence without direct authority. 

• Experience coaching and motivating individuals, building stewardship or governance capability, self-learning new subjects quickly, and forming trusted partnerships across Pfizer, particularly PGS, Digital, Finance, Quality/Regulatory, and other matrixed areas.

• Ability to travel domestically and internationally up to 10% of the year. 

• Willingness to work off hours to accommodate global time zones and support the global data steward network and cross-regional master data operations. 

• Willingness to work extended or non-standard hours during peak periods (e.g., major governance rollouts, platform go-lives, or aggressive program timelines).