Company Description LinkedIn is the world's largest professional network, built to create economic opportunity for every member of the global workforce. Our products help people make powerful connections, discover exciting opportunities, build necessary skills, and gain valuable insights every day. We're also committed to providing transformational opportunities for our own employees by investing in their growth. We aspire to create a culture that's built on trust, care, inclusion, and fun – where everyone can succeed. Join us to transform the way the world works.
Job Description
This role may be based in Sunnyvale, San Francisco, Carpinteria, New York City, Chicago, Detroit, Washington, D.C.,or Omaha. At LinkedIn, 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 LinkedIn office on select days, as determined by the business needs of the team. This role will be part of the People Analytics organization within LinkedIn's Global Talent Organization. People Analytics enables better, faster, and more strategic workforce decisions through trusted data, scalable insights, and modern analytics platforms. We are seeking a collaborative, process-minded Senior Data Governance Analyst to help operationalize LinkedIn's People Data Governance program. Reporting to the Senior Manager, People Data Governance, this role will work across the program's core areas, including the governance operating model, data certification, data quality, metadata and master data management, governance adoption, and governance automation and AI. This individual will help turn governance strategy into consistent, repeatable, and well-documented practices. They will partner across People Analytics, HR Technology, Engineering, Legal, Privacy, Security, and business functions to help ensure that people data is trusted, well-defined, consistently used, and prepared to support reporting, analytics, and emerging AI use cases.
Responsibilities
- Support the People Data Governance operating model by helping maintain clear data ownership, stewardship responsibilities, decision rights, and escalation paths.
- Partner with data owners, data stewards, analytics teams, and technical partners to document and operationalize consistent governance processes.
- Coordinate data certification activities, including defining certification requirements, documenting review criteria, tracking approvals, and maintaining certification records.
- Help establish and maintain standards for trusted data products, certified metrics, business definitions, and approved data sources.
- Support data quality processes by documenting rules, monitoring issues, coordinating remediation, and tracking quality improvements with business and technical partners.
- Partner with stakeholders to identify the business impact of data quality issues and establish appropriate ownership and resolution plans.
- Develop and maintain business glossaries, data dictionaries, metadata documentation, lineage information, ownership records, and related governance materials.
- Support master and reference data management practices that improve the consistency and usability of people data across systems and reporting solutions.
- Create repeatable governance workflows, templates, playbooks, standards, and documentation that enable teams to apply governance practices consistently.
- Facilitate working sessions, governance reviews, decision forums, and stakeholder discussions across business and technical teams.
- Support governance adoption through communications, training materials, office hours, onboarding resources, and change-management activities.
- Track governance priorities, decisions, risks, dependencies, and action items, and provide clear updates to program leaders and stakeholders.
- Partner with Legal, Privacy, Security, HR Technology, Engineering, and People Analytics teams to support responsible data access, usage, sharing, and retention practices.
- Help assess governance requirements for analytics, machine learning, and AI use cases involving people data.
- Support the development of governance automation, monitoring, and AI-enabled capabilities that improve the scalability and effectiveness of the program.
- Identify opportunities to simplify governance processes, reduce manual work, and improve the experience of data owners, stewards, producers, and consumers.
Qualifications
Basic Qualifications
- Bachelor's degree in Information Systems, Data Management, Business, Human Resources, Analytics, Computer Science, or a related field, or equivalent practical experience.
- 3+ years of experience in data governance, data management, data stewardship, data quality, metadata management, analytics, or a related discipline.
- Experience supporting or implementing data governance operating models, standards, policies, processes, or controls.
- Background documenting business definitions, data ownership, data lineage, data quality rules, or certification requirements.
- Experience coordinating work across business, analytics, and technical stakeholders.
- Ability to create process documentation, standards, templates, playbooks, or training materials.
- Experience facilitating meetings, working sessions, or decision-making discussions with cross-functional partners.
- Ability to organize and manage multiple priorities, dependencies, decisions, and follow-up items.
Preferred Qualifications
- Experience delivering technical or analytics projects in a large, matrixed organization, preferably within HR, People Analytics, or workforce-related domains.
- Hands-on experience with several of the following technologies (deep expertise in every tool is not required): SQL/T-SQL, Python, Alteryx, Power BI, Power Apps, Power Automate, and Excel-based analytical solutions.
- Experience with ETL processes and data pipelines, including data modeling, reporting and dashboard development, and data reconciliation and validation.
- Experience with cloud-based data and analytics platforms such as Databricks, Azure, or similar ecosystems.
- Familiarity with APIs and system integrations.
- Demonstrated problem-solving and troubleshooting skills, with a pragmatic, outcome-oriented approach.
- Experience establishing data ownership and stewardship models in a large, complex, matrixed organization.
- Experience with policy setting, including data standards, business rules definition, data access governance, privacy, security, retention, and responsible data-use practices.
- Familiarity with data catalog, data quality, metadata management, data lineage, or master data management tools.
- Working knowledge of SQL and HR systems, analytics, and reporting environments (e.g., Workday, Power BI, Visier, or similar) sufficient to partner effectively with technical teams.
- Understanding of how upstream HR business processes affect downstream data quality, analytics, and AI outcomes.
- Experience supporting data certification, certified metrics, semantic models, or governed reporting environments.
- Experience working with sensitive, confidential, or regulated data.
- Interest in using automation and AI to scale governance practices, and familiarity with AI data readiness concepts.
- Demonstrated documentation, facilitation, and change management skills, with the ability to make governance concepts clear and practical for non-technical audiences.
- Demonstrated stakeholder management, communication, and presentation skills, with the ability to influence without authority and drive adoption.
- Experience working in Agile delivery models such as Scrum and Kanban.
How You Will Lead You will lead through collaboration, organization, and influence. You will bring structure to complex governance work, help partners understand their responsibilities, and turn broad governance objectives into practical and repeatable processes. You can communicate clearly with technical and non-technical audiences, facilitate alignment across teams, and document decisions and requirements in a way that supports consistent execution. You are comfortable working across multiple functions and helping teams balance data accessibility, quality, privacy, security, governance, and business needs. Suggested Skills
- Data Governance
- Data Stewardship
- Data Quality
- Metadata Management
- Master Data Management
- People Analytics
LinkedIn is committed to fair and equitable compensation practices. The pay range for this role is $101,000-$164,000. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to skill set, depth of experience, certifications, and specific work location. This may be different in other locations due to differences in the cost of labor. The total compensation package for this position may also include an annual performance bonus, stock, benefits, and/or other applicable incentive compensation plans. For more information, visit https://careers.linkedin.com/benefits. Additional Information
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