Principal Architect, People Data Governance

This role will be based in Sunnyvale/Mountain View (Headquarters) Bellevue Chicago Carpinteria Detroit New York City Omaha Sunnyvale San Francisco or Washington D.C

AtLinkedIn our approach to flexible work is centered on trust andoptimizedfor culture connection clarity and the evolving needs of our work location of this role is hybrid meaning it will be performed both from home and from a LinkedIn office on select days asdeterminedby the business needs of the team.

The People Data Foundations team within People Analytics architects and stewards the enterprise HR analytics platformthe data architecture technology governance and data products that make workforce data trusted accessible secure and future-ready for analytics and AI-enabled solutions.

We are seeking a Principal Architect People Data Governance to define the strategy architecture and technical standards that govern LinkedIns people data ecosystem. This role will serve as the senior technical authority for data governance architecture across People Analytics partnering with HR Technology Data Engineering Security Privacy and AI teams to establish scalable governance capabilities that improve the quality reliability accessibility and business value of workforce data.

This is a hands-on architecture leadership role that combines technical strategy platform design governance innovation and implementation leadership. The ideal candidate will translate governance objectives into enterprise-scale solutions establish architecture standards and drive adoption of governance capabilities that support reporting analytics automation and AI-powered experiences.

Responsibilities

• Define and maintain the architecture strategy and roadmap for people data governance across the People Analytics ecosystem.
• Translate governance objectives into scalable technical designs implementation approaches and architecture standards.
• Design enterprise frameworks for metadata management data lineage stewardship certification access governance and lifecycle management.
• Establish architecture patterns that improve data quality trust consistency discoverability and accountability across workforce data domains.
• Design and implement automated data quality capabilities including monitoring anomaly detection validation frameworks SLA tracking and remediation workflows.
• Define standards for metadata management business glossaries lineage tracking cataloging and governance workflows.
• Lead architecture decisions related to governance tooling including metadata management data quality observability catalog lineage and master data management platforms.
• Partner with HR Technology Data Engineering Security Privacy Legal and AI teams to align governance requirements with enterprise architecture standards.
• Define governance-by-design principles that embed quality lineage metadata and stewardship directly into data platforms and engineering workflows.
• Architect solutions that make governance artifacts metadata lineage business definitions policies and certified data assets accessible for analytics and AI-enabled solutions.
• Establish governance controls that support responsible use of AI technologies operating on workforce data.
• Evaluate emerging governance metadata AI and data management technologies and recommend adoption strategies where appropriate.
• Provide technical leadership across governance initiatives and offer architectural guidance to engineering teams contractors and implementation partners.
• Develop reusable governance frameworks reference architectures standards templates and operational models that scale across the enterprise.

Qualifications :

Basic Qualifications

• BA/BS degree in Computer Science Information Systems Engineering Analytics Data Management or a related field or equivalent practical experience.
• 10 years of experience in data architecture data engineering data governance data platforms or related disciplines.
• Experience designing governance architectures supporting metadata management lineage stewardship data quality access controls and lifecycle management.
• Experience implementing solutions on Databricks or comparable cloud-based data platforms.
• Proficiency in SQL and Python or PySpark including development of production data workflows and automation capabilities.
• Experience designing and implementing automated metadata-driven data quality frameworks that include validation rules monitoring anomaly detection SLA management and remediation processes.
• Experience implementing metadata management data cataloging lineage or master data management capabilities.
• Experience partnering with engineering platform and architecture teams to design and deliver technical solutions.
• Experience supporting AI GenAI retrieval-augmented generation (RAG) agentic AI or related data architecture initiatives.

Preferred Qualifications

• Knowledge of data quality observability metadata management or governance platforms such as Great Expectations Deequ Monte Carlo Soda Collibra Informatica Atlan Alation Purview DataHub or similar technologies.
• Background developing or governing semantic models certified datasets or enterprise reporting assets.
• Familiarity with Visier or similar analytics platforms.
• Understanding of Workday or similar HR technology platforms including data structures calculated fields configuration approaches and integration patterns.
• Exposure to retrieval-augmented generation (RAG) architecture components including vector databases embeddings retrieval pipelines contextual ranking and metadata filtering.
• Familiarity with Model Context Protocol (MCP) tool-calling frameworks and agent-to-system interaction patterns.
• Background supporting knowledge management knowledge graph metadata graph or enterprise information architecture initiatives.
• Knowledge of HR workforce or other privacy-regulated data domains.
• Demonstrated success providing technical leadership to engineers contractors or implementation teams.
• Exposure to Go or other systems programming languages.

Leadership Expectations

• Operate as a hands-on architect who balances technical strategy with implementation guidance.
• Influence enterprise governance adoption through architecture standards frameworks and reusable patterns.
• Communicate technical concepts and architectural recommendations across engineering governance platform and business audiences.
• Evaluate technical constraints through architecture analysis platform capabilities data modeling approaches APIs and configuration options.
• Develop scalable governance capabilities that reduce operational complexity and improve long-term maintainability.
• Promote governance principles that support trusted analytics certified metrics traceable lineage and responsible AI usage.
• Drive architectural decisions that improve interoperability across people data platforms governance technologies and AI-enabled solutions.

Suggested Skills

• Data Governance
• Data Architecture
• Databricks
• Metadata Management
• AI & Data Platforms

The pay range for this role is $121000-$201000. 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 annual performance bonus stock benefits and/or other applicable incentive compensation plans. For more information visit Information :

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No

Employment Type :

Full-time