Sr. Manager, People Data Governance

Sr. Manager, People Data Governance

This role will be based in Bellevue, Chicago, Carpinteria, Detroit, New York City, Omaha, Sunnyvale, San Francisco, or Washington, D.C.

At Linked In, our approach to flexible work is centered on trust and optimized for culture, connection, clarity, and the evolving needs of our business. The work location of this role is hybrid, meaning it will be performed both from home and from a Linked In office on select days, as determined by the business needs of the team.

At Linked In, our People Analytics team empowers leaders to make better, faster, and more informed workforce decisions through trusted data, scalable reporting, and actionable insights. We are seeking a Senior Manager, People Data Governance to lead enterprise data governance efforts across the People Analytics ecosystem.

Responsibilities

• Lead the strategy, roadmap, and execution of people data governance initiatives across People Analytics and related HR data domains.
• Define and operationalize governance frameworks for data ownership, stewardship, metadata management, lineage, access governance, and lifecycle management.
• Establish standards, policies, and operating procedures that improve data quality, consistency, reliability, and usability across people data assets.
• Partner with HR Technology, Data Engineering, Legal, Privacy, Security, and business stakeholders to align governance practices with enterprise requirements.
• Develop and maintain business glossaries, data definitions, stewardship models, and governance operating processes.
• Drive data quality initiatives, including issue identification, monitoring, remediation workflows, and governance reporting.
• Lead metadata, cataloging, lineage, and data discovery efforts that enable trusted self-service analytics.
• Partner with technical teams to embed governance standards within data platforms, reporting environments, and data products.
• Support governance of sensitive employee data through classification standards, access controls, and compliance-related processes.
• Create training materials, documentation, and stakeholder engagement plans that promote governance adoption across the organization.
• Influence leaders and stakeholders to strengthen accountability for data quality, stewardship, and governance outcomes.
• Contribute to People Analytics transformation initiatives that support workforce planning, reporting modernization, automation, and AI-enabled solutions.

Qualifications

• BA/BS degree in Computer Science, Information Systems, Analytics, Data Management, Engineering, Business, or a related field, or equivalent practical experience.
• 8+ years of experience in data governance, data management, analytics, business intelligence, data engineering, or related disciplines.
• 3+ years of experience leading enterprise data governance initiatives, data quality programs, or cross-functional data transformation efforts.
• Experience developing and implementing governance frameworks covering data ownership, stewardship, metadata management, lineage, access controls, and data quality.
• Experience partnering with technical and business stakeholders to establish data standards, governance processes, and operating models.
• Experience utilizing SQL or similar data analysis tools to support data validation, issue investigation, and governance activities.

Preferred Qualifications

• Knowledge of governance practices supporting sensitive and highly regulated data domains.
• Background building trusted data foundations that support analytics, reporting, automation, and AI-enabled decision making.
• Familiarity with data catalog, metadata management, or governance platforms such as Microsoft Purview, Collibra, Alation, Atlan, Profisee, or similar solutions.
• Knowledge of cloud-based data platforms, modern data architectures, and enterprise analytics ecosystems.
• Background supporting data quality frameworks, observability programs, certification processes, and remediation workflows.
• Ability to define enterprise metrics, business glossaries, governance standards, and stewardship operating models.
• Background evaluating upstream processes and identifying opportunities to improve data quality and analytics…