Sr. Data & AI Platform Integration Architect - Raleigh, NC

At Gilead, we’re creating a healthier world for all people. For more than 35 years, we’ve tackled diseases such as HIV, viral hepatitis, COVID-19 and cancer – working relentlessly to develop therapies that help improve lives and to ensure access to these therapies across the globe. We continue to fight against the world’s biggest health challenges, and our mission requires collaboration, determination and a relentless drive to make a difference.

Every member of Gilead’s team plays a critical role in the discovery and development of life-changing scientific innovations. Our employees are our greatest asset as we work to achieve our bold ambitions, and we’re looking for the next wave of passionate and ambitious people ready to make a direct impact.

We believe every employee deserves a great leader. People Leaders are the cornerstone to the employee experience at Gilead and Kite. As a people leader now or in the future, you are the key driver in evolving our culture and creating an environment where every employee feels included, developed and empowered to fulfil their aspirations. Join Gilead and help create possible, together.

Job Description

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 & AI Platform Integration Architect, at Gilead you will...

Key Responsibilities:

Platform Governance Integration

• Integrate governance policies and metadata into AWS and Databricks environments

• Implement governance enforcement usingAWS Lake FormationandDatabricks Unity Catalog

• Implement access controls, filtering policies, and data protection rules based on governance classifications

• Integrate governance metadata and classifications from governance platforms into platform enforcement layers

• Automate the enforcement of data access controls, privacy classifications, and data retention policies within data platforms.

Data Product Enablement

• Partner with engineering teams to integrate governance requirements into data product onboarding processes

• Support secure and governed consumption of enterprise data products across analytics and AI workloads

• Ensure data products are onboarded with standardized governance enforcement patterns

Architecture & Integration Leadership

• Collaborate with Governance Enablement and Governance Capabilities teams to ensure governance policies are operationalized and enforced

• Define and implement platformlevel integration patterns that support governed analytics and AI access

• Expand 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.

Core Platform & Governance Integration

• 10+ years working with modern cloud data platforms and distributed data architectures.

• Strong understanding of enterprise data governance principles and implementation patterns.

• Experience integrating metadata, security policies, and access controls into data platforms.

• Familiarity with modern data architecture patterns such as data products, data mesh, or domain-driven data architecture.

Cloud Data Platform Architecture

• Strong working knowledge ofAWS data services(Lake Formation, S3, Glue, Lambda, EventBridge, API Gateway) andDatabricks(Unity Catalog, Delta Lake).

• Experience implementing governance enforcement using platform native controls

Integration & Automation

• Understanding of integration patterns including APIs, service architectures, and eventdriven systems

• Proficiency in Python for integration and automation engineering

Architecture & Delivery Leadership

• Architecture design experience defining and implementing highlevel integration patterns (e.g., Hub and Spoke, PeertoPeer, Data Federation)

• Strong delivery skills in Agile/Scrum environments, including backlog management and ADR documentation

Role Summary:

The Senior Data & AI Platform Integration Architect is responsible for integrating data governance controls into the enterprise Data and AI platform to ensure that enterprise data products are secure, trusted, and ready to support analytics and AI workloads. This role focuses on embedding governance policies, metadata classifications, and access controls into the data platform so that governed data can be reliably consumed by analytics systems, AI models, and intelligent agents.

This role operates as asenior individual contributor and technical leader, setting platformlevel integration patterns and governance enforcement standards. While it does not have direct people management responsibility, itprovides technical direction and design authority across multiple engineering and governance teamsand manages vendor resources supporting platform integration and implementation.  The role works at the intersection of governance, cloud data platforms, and emerging AI integration patterns.

To support trusted and AI-ready data products, the organization operates data governance throughthree complementary layersthat 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.

TheSenior Data & AI Platform Integration Architectprimarily operates within theGovernance Integrationlayer, ensuring governance policies, metadata classifications, and access controls are embedded directly within the enterprise data and AI platform.

This role collaborates closely withGovernance Enablementteams andGovernance Capabilityteams to ensure governance definitions are consistently implemented across cloud data platforms and data product workflows.

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 adata 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 Databricksforming 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 towardAI-ready data products enriched with business context, metadata, and semantic definitions.These capabilities enable intuitive discovery and interaction with enterprise data through natural language interfaces, AI-driven analytics tools, and emerging agentic AI systems.

Basic Qualifications

Bachelor's Degree and Eight Years' Experience

OR

Masters' Degree and Six Years' Experience

OR

PhD and Two Years' Experience

Preferred Qualifications

• Experience with AWS Lake Formation governance controls

• Experience with Databricks Unity Catalog governance capabilities ...