Sr. Data Governance Architect - Raleigh, NC

Gilead Sciences•Raleigh, NC

About The Position

At Gilead our pursuit of a healthier world for all people has yielded a cure for hepatitis C, revolutionary improvements in HIV treatment and prevention as well as advancements in therapies for viral and inflammatory diseases and certain cancers. We set and achieve bold ambitions in our fight against the world’s most devastating diseases, united in our commitment to confronting the largest public health challenges of our day and improving the lives of patients for generations to come. As a Senior Data Governance Architect , at Gilead you will ... 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. 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. Role Summary 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.

Requirements

Bachelor's Degree and Eight Years' Experience OR Masters' Degree and Six Years' Experience OR PhD and Two Years' Experience

Nice To Haves

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.

Responsibilities

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
Establishing metadata principles, data quality framework, and API standards that enable consistent governance across different data systems.
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

Benefits

This position may also be eligible for a discretionary annual bonus, discretionary stock-based long-term incentives (eligibility may vary based on role), paid time off, and a benefits package.
Benefits include company-sponsored medical, dental, vision, and life insurance plans.
For additional benefits information, visit: https://www.gilead.com/careers/compensation-benefits-and-wellbeing
Eligible employees may participate in benefit plans, subject to the terms and conditions of the applicable plans.

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