Executive Director, Data Management and Data Operations
Merck
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Descrizione del lavoro
Merck is seeking an Executive Director to lead Master Data Management and Data Operations. You will own the product line strategy across MDM, PLM, data governance, and data quality for Manufacturing, Quality, and Supply Chain.
You will drive operating models, budgets, and technology choices in a global, regulated environment. You will oversee data stewardship, analytics, and AI-enabled capabilities to improve data quality and operational efficiency, partnering with business and technology
Competenze
- 15+ years of progressive experience in data, digital, or technology leadership in a highly regulated industry.
- Deep expertise in master and reference data management, governance, and data quality.
- Leadership of enterprise data products and services across their lifecycle.
- Strong knowledge of manufacturing data, PLM, data platforms, and MES/LIMS/ERP/PLM.
- Proven ability to influence senior stakeholders and drive cross-functional alignment.
- Experience leading a global, matrixed organization and managing budgets.
Mansioni
- Define and execute strategy, roadmap, and investment priorities for MDM and data operations.
- Own product vision and lifecycle for data governance, quality, and integration services.
- Lead scalable data stewardship with clear ownership, standards, and metrics.
- Establish metrics and analytics to show data quality, service performance, and impact.
- Set direction for data catalogs, automation, and platform integration across domains.
- Build and mentor a global, multidisciplinary organization.
Conoscenze
Formazione
Descrizione del lavoro
The Executive Director, Master Data Management and Data Operations, serves as the Product Line Lead for the organization’s master and reference data capabilities. This senior leader in Digital Services defines and executes the strategy for master data, critical reference data, data operations, stewardship, ontology management, and data quality across Manufacturing, Quality, and Supply Chain.
The Executive Director, Master Data Management and Data Operations, serves as the Product Line Lead for the organization’s master and reference data capabilities. This senior leader in Digital Services defines and executes the strategy for master data, critical reference data, data operations, stewardship, ontology management, and data quality across 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 will build and sustain an industry-leading organization that delivers trusted, compliant, and 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 provides strategic direction and establishes priorities across product teams and delivery squads.
- Define and execute the strategy, roadmap, investment priorities, operating model, and resource plan for master and reference data management across Manufacturing, Quality, and Supply Chain.
- Own the product vision and lifecycle for Master Data Management (MDM), Product Lifecycle Management (PLM), data governance products, data quality capabilities, data operations, ontology management, and related integration services.
- Translate organizational priorities and emerging digital opportunities into a coherent portfolio of products, platforms, services, and capabilities.
- Establish and sustain a scalable data stewardship operating model with clearly defined ownership, decision rights, standards, workflows, controls, and performance measures.
- Lead the data quality function and establish preventive controls, monitoring, issue-management processes, and measurable quality standards.
- Proactively identify and resolve complex data management, ontology, and data quality challenges that affect business operations and digital strategy execution.
- Deliver reliable, high-quality data services that reduce manual remediation and operational friction while providing a consistent, user-centered experience.
- Establish metrics, reporting, and analytics that demonstrate 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 within secure and regulated environments.
- Define and maintain policies, standards, and guidelines that promote consistent adoption of data management methods, tools, and automation across user groups.
- Build, lead, and develop a high-performing, global, multidisciplinary organization with the capabilities and capacity required to deliver the product line strategy.
- Establish clear 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 trusted partnerships with business, digital, technology, and enterprise leaders to align priorities, resolve cross-functional dependencies, and drive adoption of common data management capabilities.
- Own value realization and financial performance for the product line, including budget, investment planning, total cost of ownership, vendor and contract management, benefits tracking, and OKRs.
- Establish and manage the resource model required to support 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.
- Required: Bachelor’s degree in Information Technology, Engineering, Computer Science, Data Management, or a related field.
- Preferred: MBA or master’s degree in a relevant field.
- 15+ years of progressive experience in data, digital, or technology leadership, including significant experience in the biopharmaceutical, 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 across their full 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, PLM, etc.
- 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.
- Proven 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 the ability to translate complex data and technology topics into clear decisions, priorities, and business outcomes.
- Growth mindset with a record of challenging the status quo, introducing innovative approaches, and delivering measurable improvements.
- 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.
Business Analysis, Data Science, Demand Management, Innovation, Requirements Management, Sourcing and Procurement, Stakeholder Relationship Management, Strategic Planning
Our company is committed to inclusion, ensuring that candidates can engage in a hiring process that exhibits their true capabilities.
As an Equal Employment
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