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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Sr. Data & AI Platform Integration 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:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Amazon S3, Data Analysis, Application Integration Architecture, Cloud Computing, Data as a Services, Data Architecture, Data Governance, Data Infrastructure, Data Integration, Data Retention, Data Security, Data Systems, Distributed Data Store, Data Intelligence, Python (Programming Language), Metadata, Meta-Data Management, Metadata Standards, Reference Data, Software Tools, Cloud Services, Azure Machine Learning, Service-Oriented Architecture, SQL Databases, Systems Integration, Enterprise Data Management, Cloud Platform System, Data Classification, GitHub Copilot, Large Language Models, Apigee, Data Lakes, AI Platforms, Apache Kafka, Graphql, Data Management, Api Design, Api Gateway, Restful APIs, Amazon Simple Queue Service (SQS), Domain Driven Design, Grpc, Mulesoft, Databricks - **Published:** May 14, 2026 - **Apply:** https://dejobs.org/x/x/9DA97C53C43F44B29EF7880E05F4B449/job/ ## About the Role 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 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, Bachelor's Degree and Eight Years' Experience OR Masters' Degree and Six Years' Experience OR PhD and Two Years' Experience, * 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 eventdriven 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) ## Description 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 * Automatethe 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 withGovernance Enablement and Governance Capabilitiesteams 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+ yearsworking 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., 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 platformlevel 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., *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 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 - [Blueprints for Success: Steering a Global Data & AI Architecture](https://www.wearedevelopers.com/videos/1577-blueprints-for-success-steering-a-global-data-ai-architecture) - [Exploring the Power of gRPC-Gateway for Writing RESTful Services](https://www.wearedevelopers.com/videos/2072-exploring-the-power-of-grpc-gateway-for-writing-restful-services) - [Putting the Graph In GraphQL With The Neo4j GraphQL Library](https://www.wearedevelopers.com/videos/257-putting-the-graph-in-graphql-with-the-neo4j-graphql-library) - [Boosting OpenSearch Performance: gRPC Search in Action](https://www.wearedevelopers.com/videos/1935-boosting-opensearch-performance-grpc-search-in-action) - [GraphQL + Apollo + Next.js: A Lovely Trio](https://www.wearedevelopers.com/videos/311-graphql-apollo-next-js-a-lovely-trio) - [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) ## Related Articles - [Got AI ideas but no money? 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