Sr. Data & AI Platform Integration 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 & 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 using AWS Lake Formation and Databricks 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 Automat e 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 platform level 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 of AWS data services (Lake Formation, S3, Glue, Lambda, EventBridge , API Gateway) and Databricks (Unity Catalog, Delta Lake). Experience implementing governance enforcement using platform native controls Integration & Automation Understanding of integration patterns including APIs, service architectures, and event driven systems Proficiency in Python for integration and automation engineering Architecture & Delivery Leadership Architecture design experience defining and implementing high level integration patterns (e.g., Hub and Spoke, Peer to Peer, 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 a senior individual contributor and technical leader , setting platform level integration patterns and governance enforcement standards. While it does not have direct people management responsibility, it provides technical direction and design authority across multiple engineering and governance teams and 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 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 & AI Platform Integration Architect primarily operates within the Governance Integration layer, ensuring governance policies, metadata classifications, and access controls are embedded directly within the enterprise data and AI platform. This role collaborates closely with G overnance E nablement teams and G overnance C apability teams 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 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 . These capabilities enable intuitive discovery and interaction with enterprise data through natural language interfaces, AI-driven analytics tools, and emerging agentic AI systems.

Requirements

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.
Strong working knowledge of AWS data services (Lake Formation, S3, Glue, Lambda, EventBridge , API Gateway) and Databricks (Unity Catalog, Delta Lake).
Experience implementing governance enforcement using platform native controls
Understanding of integration patterns including APIs, service architectures, and event driven systems
Proficiency in Python for integration and automation engineering
Architecture design experience defining and implementing high level integration patterns (e.g., Hub and Spoke, Peer to Peer, Data Federation)
Strong delivery skills in Agile/Scrum environments, including backlog management and ADR documentation
Bachelor's Degree and Eight Years' Experience OR Masters' Degree and Six Years' Experience OR PhD and Two Years' Experience

Nice To Haves

Experience with AWS Lake Formation governance controls
Experience with Databricks Unity Catalog governance capabilities
Familiarity with governance platforms such as Informatica IDMC
Experience supporting analytics and AI workloads in cloud data platforms
Strong knowledge of API design patterns (REST, GraphQL , gRPC ) and API management platforms (AWS API Gateway, Apigee, MuleSoft, or equivalent)
Experience with event driven architecture and message streaming platforms (Apache Kafka, Amazon MSK, EventBridge , SQS/SNS)
Experience designing integration solutions for AI/ML platforms or agentic architectures, including LLM API patterns and MCP based agent tooling
Familiarity with emerging AI and agent integration patterns
Working knowledge of AI assisted software development tools (GitHub Copilot, Claude, or equivalent)

Responsibilities

Integrate governance policies and metadata into AWS and Databricks environments
Implement governance enforcement using AWS Lake Formation and Databricks 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
Automat e the enforcement of data access controls, privacy classifications, and data retention policies within data platforms.
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
Collaborate with Governance Enablement and Governance Capabilities teams to ensure governance policies are operationalized and enforced
Define and implement platform level 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.

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.

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