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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Principal Architect, People Data Governance - **Company:** LinkedIn Corporation - **Location:** Mountain View, CA, United States - **Experience:** Expert - **Salary:** $121,000.0 - $201,000.0 - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Business Analytics Applications, Data Analysis, Computing Platforms, Information Systems, Data Architecture, Information Engineering, Data Governance, Data Structures, Graph Database, HR Analytics, Identity and Access Management, Python (Programming Language), Knowledge Management, Metadata, Meta-Data Management, Operational Databases, SQL Databases, System Programming, Cloud Platform System, Generative AI, Pyspark, Information Technology, Data Lineage, Collibra, Data Management, Virtual Agents, Workday, Databricks - **Published:** July 26, 2026 - **Apply:** https://www.juju.com/job/00000000gjn98z ## About the Role + 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. ## Description We are seeking a Principal Architect, People Data Governance to define the strategy, architecture, and technical standards that govern LinkedIn's 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., A request for an accommodation will be responded to within three business days. However, non-disability related requests, such as following up on an application, will not receive a response. LinkedIn will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant. However, employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by LinkedIn, or (c) consistent with LinkedIn's legal duty to furnish information. San Francisco Fair Chance Ordinance Pursuant to the San Francisco Fair Chance Ordinance, LinkedIn will consider for employment qualified applicants with arrest and conviction records. Pay Transparency Policy Statement As a federal contractor, LinkedIn follows the Pay Transparency and non-discrimination provisions described at this link: https://lnkd.in/paytransparency. ## Related Videos - [Blueprints for Success: Steering a Global Data & AI Architecture](https://www.wearedevelopers.com/videos/1577-blueprints-for-success-steering-a-global-data-ai-architecture) - [PySpark - Combining Machine Learning & Big Data](https://www.wearedevelopers.com/videos/44-pyspark-combining-machine-learning-big-data) - [Destigmatizing the Workplace: Building Real Inclusion](https://www.wearedevelopers.com/videos/1492-destigmatizing-the-workplace-building-real-inclusion) - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [Beyond GPT: Building Unified GenAI Platforms for the Enterprise of Tomorrow](https://www.wearedevelopers.com/videos/1525-beyond-gpt-building-unified-genai-platforms-for-the-enterprise-of-tomorrow) - [Empowering Retail Through Applied Machine Learning](https://www.wearedevelopers.com/videos/976-empowering-retail-through-applied-machine-learning) ## Related Articles - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [Stephan Gillich - Bringing AI Everywhere](https://www.wearedevelopers.com/magazine/489-stephan-gillich-bringing-ai-everywhere)