> Markdown version of [/jobs/ext/277505-sr-data-governance-architect-raleigh-nc](https://www.wearedevelopers.com/jobs/ext/277505-sr-data-governance-architect-raleigh-nc). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Sr. Data Governance Architect - Raleigh, NC - **Company:** Gilead Sciences Inc. - **Location:** Raleigh, NC, United States - **Experience:** Expert - **Salary:** $146,200.0 - $189,200.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Amazon Web Services, Cloud Computing, Data Governance, Data Security, Data Systems, Data Intelligence, Metadata, Meta-Data Management, Metadata Standards, Reference Data, SQL Databases, Enterprise Data Management, Data Classification, AI Platforms, Collibra, Data Management, Databricks - **Published:** May 19, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=d55a296ed9b5027b ## About the Role Bachelor's Degree and Eight Years' Experience OR Masters' Degree and Six Years' Experience OR PhD and Two Years' Experience Preferred Qualifications: * 10+ years' experience in data governance, data management. * Deep understanding of data management principles, frameworks, and methodologies * Experience implementing enterprise data governance or stewardship programs * Experience with governance platforms such as Informatica, Collibra, or Alation. * Strong understanding of governance frameworks, CDEs, and data quality practices * Ability to engage business stakeholders and facilitate governance workshops * Strong communication and stakeholder management skills * Experience working in regulated industries such as pharmaceuticals or healthcare * Knowledge of data protection regulations such as GDPR or CCPA * Experience supporting governance initiatives that enable analytics and AI-driven use cases. * Understanding of data product operating models or data mesh concepts. People Leader Accountabilities: * Create Inclusion - knowing the business value of diverse teams, modeling inclusion, and embedding the value of diversity in the way they manage their teams. * Develop Talent - understand the skills, experience, aspirations and potential of their employees and coach them on current ## Description Governance Enablement & Stewardship * Partner with business domains to establish data ownership and stewardship for enterprise data products * Facilitate governance workshops to identify critical data elements and governance requirements * Establish stewardship communities responsible for maintaining trusted data assets * Define stewardship responsibilities for metadata completeness, data quality, and data classification Metadata, Data Quality & Classification * Establish metadata principles, data quality framework, and API standards that enable consistent governance across different data systems * Collaborate with business stakeholders to define businessfriendly data quality rules * Ensure governance definitions are documented within governance platforms * Partner with domain teams to classify sensitive data such as personal data, sensitive personal data, healthrelated information, and HR sensitive data * Ensure data products contain sufficient metadata and business context to support analytics and AIdriven use cases Collaboration & Operationalization * Collaborate with Governance Capabilities and Governance Integration teams to operationalize governance practices Role Summary: The Senior Data Governance Architect is responsible for designing and enabling enterprise data governance practices that ensure data products are trusted, well-described, and aligned with organizational policies and regulatory requirements. This role works closely with business domains and platform teams to define governance requirements, establish governance standards, and ensure enterprise data assets are ready to support analytics and AI use cases. This role operates as a senior individual contributor and data governance architect, defining enterprise governance standards, metadata requirements, and stewardship practices. While it does not have direct people management responsibility, it provides governance leadership and direction across business domains, partners closely with platform and integration teams, and manages vendor resources supporting governance enablement and implementation. To support trusted and AI-ready data products, the organization operates data governance through three complementary layers that ensure governance is defined, supported by technology, and enforced across the enterprise data and AI platform. 1. Governance Enablement This layer activates governance practices across business domains by defining governance requirements such as critical data elements, metadata standards, data quality rules, and data classification. It ensures enterprise data products are properly described, governed, and aligned with business and regulatory needs. 2. Governance Capabilities This layer provides the technology and operational capabilities that support governance across the enterprise. These capabilities enable metadata management, governance policy management, data quality monitoring, and trusted data product discovery. 3.Governance Integration This layer ensures governance policies and metadata classifications are operationalized within the enterprise data and AI platform so that governed data can be reliably used for analytics and AI applications. Together, these layers ensure enterprise data products are trusted, discoverable, and ready to support analytics and AI initiatives. The Senior Data Governance Architect primarily operates within the Governance Enablement layer, working with business domains and platform teams to define governance requirements and ensure enterprise data products contain the metadata, quality standards, and classifications required to support trusted analytics and AI use cases. This role collaborates closely with teams responsible for Governance Capabilities and Governance Integration to ensure governance definitions are consistently operationalized across the enterprise data ecosystem. About Our Data & AI Platform Our organization operates a modern enterprise data and AI ecosystem designed to enable trusted, governed, AI-ready data products that support advanced analytics and emerging AI-driven use cases. The platform is based on a data mesh architecture, where business domains publish reusable data products that can be securely discovered and consumed across the enterprise. Our enterprise data and AI platform technology stack includes: * AWS and Databricks forming the enterprise cloud data and AI platform * Informatica Intelligent Data Management Cloud (IDMC) supporting metadata management, data marketplace, governance policies, and business data quality rules * IDMC Master Data Management (MDM) and Reference Data Management (RDM) managing core enterprise business entities Enterprise data governance plays a central role in this ecosystem by ensuring that data products are trusted, well-documented, and governed for responsible use across analytics and AI initiatives. As the platform evolves, we are expanding beyond traditional SQL-based data access toward AI-ready data products enriched with business context, metadata, and semantic definitions that enable intuitive discovery and interaction with enterprise data through natural language interfaces, AI-driven analytics tools, and emerging agentic AI systems., performance and future potential. They ensure employees are receiving the feedback and insight needed to grow, develop and realize their purpose. * Empower Teams - connect the team to the organization by aligning goals, purpose, and organizational objectives, and holding them to account. They provide the support needed to remove barriers and connect their team to the broader ecosystem. ## Related Videos - [A Data Mesh needs Open Metadata](https://www.wearedevelopers.com/videos/505-a-data-mesh-needs-open-metadata) - [Cutting LLM Costs Without Cutting Quality: How to Beat Proprietary LLMs with Fine-Tuned Open Source](https://www.wearedevelopers.com/videos/100151-cutting-llm-costs-without-cutting-quality-how-to-beat-proprietary-llms-with-fine-tuned-open-source) - [Blueprints for Success: Steering a Global Data & AI Architecture](https://www.wearedevelopers.com/videos/1577-blueprints-for-success-steering-a-global-data-ai-architecture) - [Crafting Custom Frameworks with Rust: A Deep Dive into Procedural Macros](https://www.wearedevelopers.com/videos/849-crafting-custom-frameworks-with-rust-a-deep-dive-into-procedural-macros) - [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) - [OLTP in the Lakehouse: Redefining Data for AI Workloads](https://www.wearedevelopers.com/videos/2038-oltp-in-the-lakehouse-redefining-data-for-ai-workloads) ## Related Articles - [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) - [Got AI ideas but no money? Here are 10 free ways to level up your AI skills with Google Cloud](https://www.wearedevelopers.com/magazine/600-got-ai-ideas-but-no-money-here-are-10-free-ways-to-level-up-your-ai-skills-with-google-cloud) - [Stephan Gillich - Bringing AI Everywhere](https://www.wearedevelopers.com/magazine/489-stephan-gillich-bringing-ai-everywhere) - [Data Analyst Salary in the UK](https://www.wearedevelopers.com/magazine/278-data-analyst-salary-in-the-uk) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk)