What are the responsibilities and job description for the Head of Intelligence Products position at Eleks?
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
- 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
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.