Lead strategy, architecture, and operating model for an enterprise AI-ready data platform. Define semantic models, knowledge graph and ontology standards, data governance, APIs, and commercialization for reusable intelligence products. Drive platform evolution, technology selection, cross-functional partnerships, and build a high-performing data architecture and engineering team supporting LLMs, RAG, vector search, and regulated environments.
ELEKS is looking for a Head of Intelligence Products in the United States.
Our customer is building a next-generation AI platform that enables organizations to securely develop, govern, and operationalize artificial intelligence while ensuring that sensitive data and organizational knowledge remain fully under their control. The platform combines advanced AI capabilities with enterprise-grade governance, security, and data sovereignty to support mission-critical decision-making.
The solution serves government organizations, NGOs, and enterprise customers operating in highly regulated and security-sensitive environments, where reliability, accountability, and trust are essential.
REQUIREMENTS
- 10+ years of experience in Data Engineering, Data Architecture, Platform Engineering, or related leadership roles
- Proven experience building and scaling modern cloud-based data platforms in enterprise environments
- Strong expertise with Snowflake, lakehouse architectures, graph databases, vector databases, and modern data platforms
- Deep understanding of knowledge graphs, ontology design, semantic modeling, metadata management, and enterprise data architecture
- Experience building AI-ready data platforms supporting LLMs, Retrieval-Augmented Generation (RAG), vector search, and AI applications
- Experience designing enterprise APIs, developer platforms, and data products for external customers
- Strong knowledge of data governance, lineage, privacy, security, and enterprise access control
- Experience defining enterprise data strategy and leading architecture decisions
- Hands-on experience with modern ETL/ELT pipelines, orchestration frameworks, and production data services
- Experience working with cross-functional Product, Engineering, AI, and Commercial teams
- Strong leadership, stakeholder management, and communication skills
- Experience building and leading high-performing technical teams
- Upper-Intermediate or higher level of English
RESPONSIBILITIES
- Define and lead the enterprise intelligence product strategy, architecture, and operating model
- Drive the evolution of a modern enterprise data platform supporting AI, analytics, and commercial data products
- Design scalable data architecture, semantic models, and knowledge graph capabilities
- Define enterprise ontology, metadata, governance, and interoperability standards
- Lead the development of AI-ready data services, APIs, and developer-facing platforms
- Define architecture supporting structured, semi-structured, and unstructured data at scale
- Partner with Engineering, AI, Product, and Commercial teams to transform data assets into reusable intelligence products
- Establish standards for data quality, lineage, provenance, security, and lifecycle management
- Define commercialization requirements for enterprise data products, including APIs, licensing models, access control, SLAs, and observability
- Evaluate and recommend technologies across cloud data platforms, graph databases, vector stores, orchestration, and AI infrastructure
- Lead architecture decisions supporting AI-native applications, LLM integrations, and semantic search capabilities
- Build and mentor a high-performing team of data architects, engineers, and platform specialists
- Act as a strategic technical advisor for executive stakeholders and drive long-term data platform vision
Similar Jobs
Cloud • Software • Database • Analytics
The Head of Data Intelligence Products will define and execute product strategy, lead a global team, oversee AI developments, and engage CDOs to modernize data management.
Top Skills:
Ai AgentsAi/MlCloud-Native ArchitectureData CatalogData GovernanceData IntelligenceData MeshData QualityLlmsModern Data Stack
Cloud • Fintech • Software • Business Intelligence • Consulting • Financial Services
Lead client engagements to assess business challenges, define enterprise data and AI strategies, develop roadmaps, guide solution design and delivery, provide technical leadership and mentoring, and support practice growth via presales and thought leadership.
Top Skills:
AnalyticsAzureBusiness IntelligenceCloud Data PlatformsCopilotsData AgentsData WarehousingDatabricksGenerative AiMicrosoft FabricSnowflake
Artificial Intelligence • Consumer Web • Edtech • Enterprise Web • HR Tech • Social Impact • Generative AI
Own new business, renewals, and expansion across an assigned territory in higher education. Prospect and sell to senior education leaders, build pipeline, hit quotas, manage contracts, collaborate with Customer Success to drive measurable outcomes, and identify cross-sell opportunities. Travel approximately 25% for meetings and events.
What you need to know about the San Francisco Tech Scene
San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.
Key Facts About San Francisco Tech
- Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Google, Apple, Salesforce, Meta
- Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
- Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
- Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine



