Ontology, Knowledge Graph & Semantic Layer Lead

Job description

the employer is currently looking for an Ontology, Knowledge Graph & Semantic Layer Lead for one of our partners, an IT Services and IT Consulting company. The role defines, designs and leads the first implementation of an enterprise ontology, knowledge graph and semantic layer programme. This is a foundational, strategic role for someone who pairs deep hands on semantic technology expertise with enterprise architecture experience, and who has already delivered ontology and knowledge graph programmes at scale. You’ll set the target state, build the roadmap and governance, and get the first capabilities live. Key responsibilities include: defining the target state architecture and strategy for the enterprise ontology, knowledge graph and semantic layer, designing enterprise semantic models, taxonomies and ontologies aligned with business and data domains, building the roadmap, governance framework, standards and operating model, leading the initial implementation phases and guiding the build of foundational ontology and knowledge graph capabilities, identifying and prioritising business use cases and quick wins, aligning the programme with Data Governance, Metadata Management, MDM, Data Products, Data Catalog and AI initiatives, advising on tooling, platform selection and architecture decisions, building internal capability through knowledge transfer and mentoring.

Requirements

• 10+ years in Data Architecture, Semantic Technologies, Knowledge Engineering and Knowledge Management · Proven experience leading enterprise scale ontology initiatives, knowledge graph implementations and semantic architecture programmes · Strong grounding in ontology engineering, taxonomy development, knowledge representation, semantic modelling and metadata management · Experience defining target state enterprise semantic architectures · Solid understanding of Data Governance, Metadata Management, Enterprise Architecture and Business Architecture · Experience using ontologies and knowledge graphs to power AI, GenAI, RAG, enterprise search and knowledge management · Deep experience with several of: RDF, OWL, RDFS, SKOS, SPARQL, SHACL, property graphs, LPG and RDF graph models, semantic reasoning and inferencing · Hands on experience with knowledge graph platforms such as Stardog, GraphDB, TopBraid, PoolParty, Neo4j, Amazon Neptune, Microsoft Fabric / Purview semantic capabilities or the Databricks knowledge graph ecosystem · Excellent stakeholder management, with the ability to engage both executive and technical audiences

Skills