11 of 11 Permanent SPARQL Jobs in England

/OWL ontologies in production (not solely academic — you have shipped something real) SHACL for constraint validation, data quality enforcement, and shape‐based governance SPARQL 1.1 — fluent in complex queries, property paths, and federated queries At least one enterprise triple store/graph platform: TopBraid, GraphDB (Ontotext), Stardog, RDFox, Amazon ...

experience with: OWL (Web Ontology Language) RDF (Resource Description Framework) SKOS (Simple Knowledge Organization System) SHACL (Shapes Constraint Language) Semantic Web standards and technologies SPARQL, Linked Data Experience developing, managing, and governing: Controlled Vocabularies Taxonomies Business Glossaries Semantic Standards Knowledge and Domain Expertise Strong understanding of: Semantic Interoperability Metadata Management ...

with the team. BASIC (REQUIRED) QUALIFICATION Bachelor's degree or equivalent, plus at least 3 of the following: Experience with Knowledge Graph technologies (RDF, SPARQL, LPG, SHACL) Experience in schema design, ontology management, and KG curation Expertise in designing and developing KG solutions and graph‐based ML models (functional + ...

team. Qualification Basic (Required) Qualification Bachelor's degree or equivalent, plus at least 3 of the following: Experience with Knowledge Graph technologies (RDF, SPARQL, LPG, SHACL) Experience in schema design, ontology management, and KG curation Expertise in designing and developing KG solutions and graph-based ML models (functional + technical ...

shares with the team.BASIC (REQUIRED) QUALIFICATIONBachelor's degree or equivalent, plus at least 3 of the following:Experience with Knowledge Graph technologies (RDF, SPARQL, LPG, SHACL)Experience in schema design, ontology management, and KG curationExpertise in designing and developing KG solutions and graph-based ML models (functional + technical)Experience ...

modeling)Ontology Engineering (OWL/RDF, Protégé)Graph RAG (LLM integration, retrieval strategies)API Design (REST/GraphQL)Preferred SkillsGraph platforms: Neptune, TigerGraphSemantic standards: SPARQL, SHACLAI/ML and LLM ecosystem exposureData governance and integration experienceSummaryThis role is pivotal in shaping the semantic foundation for enterprise AI, bridging data architecture ...

comprehensive metadata; Experience in creating and managing data using RDBMS or No SQL, writing ETL processes and retrieving data using languages such as SQL, SPARQL, Xpath etc, with knowledge of event-driven architecture patterns including publish-subscribe and data streaming; Experience in leading on, or playing a major role ...

involves configuring graph databases or triple stores, populating the knowledge graph with data (RDF triples), and optimizing it for query performance and scalability.Semantic Querying (SPARQL): Create and optimize SPARQL queries to enable efficient retrieval, integration, and analysis of data from the knowledge graph. You will develop semantic queries and endpoints … semantic web technologies and standardsspecifically, hands-on proficiency with OWL (Web Ontology Language) and RDF (Resource Description Framework) for ontology modelling, as well as SPARQL for querying graph data.Knowledge Graph Experience: Practical experience building or maintaining knowledge graphs or linked data systems in an enterprise setting.Data Modelling & Integration Skills ...

both — you know what's worth automating and why. • Comfortable working directly with a Python codebase — building, debugging, and extending features. • Graph literacy — Neo4j, SPARQL, or equivalent. Can inspect a knowledge graph and judge its fitness. • Agent fluency — has built LLM agents in production. Knows what goes wrong. • Strong communicator ...

knowledge graphs and ontologies. Strong understanding of graph data modelling, semantic modelling, and ontology design. Experience with graph database platforms and query languages (e.g. SPARQL, Cypher, or equivalent). Data engineering fundamentals: pipelines, data preparation, and integration with enterprise systems (ERP, CRM, operational systems). Ability to translate data ...

risk, supply chain, compliance) Build ingestion pipelines (ETL/streaming/CDC) and entity resolution for graph population Author complex queries (Cypher, GSQL, AQL, SPARQL etc. depending on stack) Integrate knowledge graph retrieval & reasoning into LLM/RAG/GraphRAG systems Develop and evaluate graph ML/embedding models (link … roles Deep experience with at least one graph technology: Neo4j, TigerGraph, ArangoDB, OrientDB, or Stardog Proficiency in query languages (Cypher, GSQL, AQL, SPARQL, etc.) Strong background in pipelines, ETL, and entity resolution Exposure to integrating KG + LLM or RAG architectures Experience with graph algorithms, embeddings, or GNNs Cloud & production ...