At a Glance
- Tasks: Design and maintain enterprise ontologies and knowledge graphs to enhance data understanding.
- Company: Join a forward-thinking company revolutionising knowledge management with semantic technologies.
- Benefits: Competitive salary, flexible working options, and opportunities for professional growth.
- Other info: Dynamic role with potential for significant impact on enterprise-wide data strategies.
- Why this job: Shape the future of AI and data ecosystems while driving innovation in a collaborative environment.
- Qualifications: Experience with OWL, RDF, and strong collaboration skills with business and technical teams.
The predicted salary is between 60000 - 80000 £ per year.
We're looking for an experienced Senior Semantic Engineer to help shape the future of enterprise knowledge management through semantic technologies, ontologies, and knowledge graphs. This is an exciting opportunity for a specialist who is passionate about creating structured, interconnected data ecosystems that power intelligent applications, AI solutions, and enterprise-wide data understanding.
As a Senior Semantic Engineer, you will design and maintain enterprise ontologies and knowledge graphs that provide a shared understanding of data across the organisation. Working closely with Data, AI, Engineering, and Business teams, you'll help transform disconnected data into meaningful, connected knowledge that drives innovation, improves decision-making, and enhances AI capabilities.
What You'll Be Doing
- Design, develop, and maintain enterprise ontologies using OWL, RDF, and related semantic technologies
- Collaborate with business and domain experts to model real-world concepts, entities, and relationships
- Build and manage enterprise knowledge graphs that connect and enrich data from multiple sources
- Configure, maintain, and optimise graph databases and triple stores for performance and scalability
- Develop and optimise SPARQL queries to support analytics, search, and knowledge discovery
- Define and enforce semantic validation rules using technologies such as SHACL and OWL constraints
- Establish standards for data quality, consistency, interoperability, and governance
- Integrate semantic models into enterprise systems, APIs, applications, and data platforms
- Work alongside Data Architects and Engineers to embed semantic capabilities into enterprise workflows
- Partner with AI and Machine Learning teams to enhance LLM and AI-driven solutions with semantic context
- Support the use of knowledge graphs for intelligent agents, reasoning engines, contextual search, and retrieval
- Produce documentation, training materials, and best practice guidance to drive adoption across the organisation.
Key Skills
