Executive Director, Data Management and Data Operations

Merck•Cambridge, MA

3d•$255,800 - $402,700•Hybrid

About The Position

The Executive Director, Master Data Management and Data Operations serves as the Product Line Lead for the organization’s master and reference data capabilities within Digital Services. This senior leader defines and executes strategy across master data, critical reference data, data operations, stewardship, ontology management, and data quality for Manufacturing, Quality, and Supply Chain. The role has end-to-end accountability for the product line vision, roadmap, services, enabling technologies, operating model, resource strategy, and total cost of ownership. The leader builds and sustains an organization that delivers trusted, compliant, fit-for-purpose master data; improves operational efficiency and user experience; accelerates digital, analytics, and AI solutions; and creates measurable business value. Reporting to the Associate Vice President of Digital Services in Global Manufacturing, Quality, Supply Chain & Innovation, the role sets strategic direction and priorities across product teams and delivery squads. The position leads product and operational capabilities spanning Master Data Management, Product Lifecycle Management, data governance, data quality, data operations, ontology management, and related integration services. It also leads a global multidisciplinary organization, manages product-line financial performance and partnerships, and promotes adoption of consistent data-management practices in a regulated environment.

Requirements

Bachelor’s degree in Information Technology, Engineering, Computer Science, Data Management, or a related field.
15 or more years of progressive experience in data, digital, or technology leadership, including significant experience in biopharmaceuticals, life sciences, manufacturing, or another highly regulated industry.
Deep expertise in master and reference data management, data stewardship, data governance, data quality, ontology management, or related enterprise data capabilities.
Demonstrated leadership of enterprise data products, platforms, and services throughout their lifecycle, from strategy and design through implementation, adoption, sustainment, and value realization.
Strong knowledge of manufacturing-related master and reference data, Product Lifecycle Management, data platforms, and the needs of Manufacturing, Quality, and Supply Chain.
Proven experience with business domain applications such as MES, LIMS, Veeva Quality, Supply Planning, ERP, or PLM.
Experience leading a sizable multidisciplinary organization, including organizational design, talent development, coaching, succession planning, and capability building.
Demonstrated accountability for significant budgets, investment portfolios, financial planning, vendor performance, and total cost of ownership.
Ability to influence senior stakeholders, align organizations on complex technical and business decisions, resolve cross-functional dependencies, and drive accountability.
Experience leading enterprise transformation and adoption in a global, matrixed environment.
Experience with Agile and Scrum delivery models, product management, and product owner responsibilities.
Strong executive communication skills and ability to translate complex data and technology topics into clear decisions, priorities, and business outcomes.
Growth mindset and a record of challenging the status quo, introducing innovative approaches, and delivering measurable improvements.
Business Analysis, Data Science, Demand Management, Innovation, Requirements Management, Sourcing and Procurement, Stakeholder Relationship Management, and Strategic Planning.

Nice To Haves

MBA or master’s degree in a relevant field.
Experience in global technology centers or geographically distributed delivery organizations.
Experience applying lean, agile, and people-centered design techniques to create inclusive technical and non-technical experiences and communications.
Experience in manufacturing, GxP, or other regulated environments.
Demonstrated experience applying AI, advanced analytics, or automation to improve data quality, stewardship, metadata management, or data operations.
Experience evaluating and implementing generative or agentic AI capabilities within governed, secure, and regulated data environments.

Responsibilities

Define and execute strategy, roadmap, investment priorities, operating model, and resource plans for master and reference data management across Manufacturing, Quality, and Supply Chain.
Own the product vision and lifecycle for MDM, PLM, data governance products, data quality capabilities, data operations, ontology management, and related integration services.
Translate organizational priorities and digital opportunities into a coordinated portfolio of products, platforms, services, and capabilities.
Establish and sustain a scalable data stewardship operating model with defined ownership, decision rights, standards, workflows, controls, and performance measures.
Lead the data quality function, establishing preventive controls, monitoring, issue management, and measurable quality standards.
Identify and resolve complex data management, ontology, and data quality challenges affecting business operations and digital strategy execution.
Deliver reliable, high-quality data services that reduce manual remediation and operational friction and provide a consistent, user-centered experience.
Establish metrics, reporting, and analytics for data quality, service performance, adoption, compliance, and business impact.
Set direction for MDM platforms, PLM capabilities, data catalogs, integration services, automation, methods, and tools in alignment with business and enterprise technology strategies.
Apply AI-enabled capabilities to improve data quality monitoring, issue detection, root-cause analysis, remediation, and prevention in secure and regulated environments.
Define and maintain policies, standards, and guidelines promoting consistent adoption of data management methods, tools, and automation.
Build, lead, and develop a high-performing global multidisciplinary organization with the capabilities and capacity needed to deliver the product line strategy.
Establish accountabilities across product teams and squads; coach and mentor leaders and team members; and develop succession and capability-building plans.
Lead organizational change and adoption to embed common data management practices, standards, and ways of working.
Build partnerships with business, digital, technology, and enterprise leaders to align priorities, resolve cross-functional dependencies, and drive adoption.
Own product-line value realization and financial performance, including budget, investment planning, total cost of ownership, vendor and contract management, benefits tracking, and OKRs.
Establish and manage the resource model supporting master data management across divisional platforms and business processes.
Align systems development structures, platforms, methods, and tools with business strategy, regulatory expectations, and emerging digital opportunities.