Sr. Data Governance Analyst

LinkedIn•Sunnyvale, CA

3d•Hybrid

About The Position

This role will be based in Bellevue, Chicago, Carpinteria, Detroit, New York City, Omaha, Sunnyvale, San Francisco, or Washington, D.C. 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 the Global Talent Organization (GTO) at LinkedIn. People Analytics enables better, faster, and more strategic workforce decisions through trusted data, scalable insights, and modern analytics platforms. We are seeking a highly collaborative and technically strong Data Governance professional to help build and operationalize the next generation of People Data Governance capabilities. This role will partner closely with People Analytics, Engineering, HR Technology, Data Science, Security, Privacy, and business stakeholders to establish trusted, scalable, and AI-ready workforce data foundations. This position goes beyond traditional governance execution and will help shape how enterprise people data is structured, governed, standardized, and operationalized to support modern analytics, automation, and emerging AI use cases. The ideal candidate will combine strong governance expertise with hands-on technical acumen and an understanding of how upstream business processes influence downstream analytics and AI outcomes. The successful candidate will help drive governance maturity across data ownership, stewardship, metadata management, observability, semantic modeling, and data quality management while enabling scalable and compliant consumption of workforce data across the enterprise.

Requirements

BA/BS degree in Computer Science, Information Systems, Analytics, Engineering, or related field
5+ years of experience in Data Governance, Data Management, Analytics Engineering, or related enterprise data disciplines
8+ years of overall experience in Data, Analytics, Business Intelligence, or Technology functions

Nice To Haves

Experience implementing or supporting enterprise Data Governance programs, preferably within HR, People Analytics, or workforce-related domains
Strong understanding of modern Data Governance principles including stewardship, ownership, metadata management, lineage, observability, and data quality management
Experience supporting AI-ready data ecosystems through standardized data foundations, semantic modeling, metadata enrichment, and scalable governance practices
Ability to think beyond downstream reporting and evaluate how upstream business processes, workflows, and operational behaviors influence data quality and AI effectiveness
Strong proficiency in SQL/T-SQL and experience working with databases, semantic layers, and enterprise analytics environments
Experience with cloud-based data platforms, ETL/data pipelines, and modern data architecture patterns
Experience with data governance, metadata management, observability, catalog, or master data management tools (e.g., Profisee or similar platforms)
Familiarity with Power BI, DAX, SSAS, reporting frameworks, and semantic modeling concepts
Experience defining enterprise metrics, business rules, governance workflows, and standardized reporting definitions
Experience supporting enterprise data access governance, security frameworks, and compliance-related data controls
Strong problem-solving, stakeholder management, communication, and executive presentation skills
Ability to influence cross-functional teams and drive governance adoption across large, matrixed organizations
Experience working in Agile delivery models including Scrum and Kanban frameworks
Strong understanding of data requirements supporting analytics, workforce planning, business intelligence, automation, and AI enablement

Responsibilities

Partner with functional teams, HR Technology, Engineering, Legal, Privacy, and Security teams to define and operationalize enterprise data governance policies, standards, and stewardship models
Help establish scalable governance frameworks that improve trust, consistency, accessibility, compliance, and usability of workforce data across reporting, analytics, automation, and AI-driven use cases
Drive governance initiatives focused on foundational AI readiness, including trusted data structures, standardized definitions, metadata enrichment, lineage visibility, and scalable semantic models
Evaluate and improve upstream business processes and data capture mechanisms to ensure enterprise systems produce high-quality, reliable, and AI-consumable data
Partner with cross-functional stakeholders to define enterprise metric standards, business glossary definitions, ownership models, and stewardship accountability frameworks
Support enterprise metadata management, cataloging, taxonomy management, lineage documentation, and semantic layer governance initiatives
Define and operationalize data quality management practices including observability, issue triage, remediation workflows, SLA management, and certification processes
Collaborate with data scientists, analytics teams, and engineering organizations to translate business requirements into scalable governance-enabled data solutions
Support the development of governance knowledge management capabilities including training, governance documentation, playbooks, operating procedures, and adoption frameworks
Work with structured and unstructured datasets across enterprise HR systems, analytics platforms, and cloud-based ecosystems
Develop and analyze SQL-based queries and semantic models to validate data integrity, reconcile metrics, and support governance controls
Partner with Engineering and platform teams to support implementation of modern cloud-based data ecosystems, governance tooling, and master data management solutions
Support access governance and data security processes including documentation of enterprise access models, sensitive data handling standards, and governance controls
Contribute to governance-related transformation programs supporting workforce planning, reporting modernization, analytics enablement, and AI-driven operational capabilities
Operate effectively within Agile delivery frameworks including Scrum and Kanban models while managing multiple cross-functional priorities