17 of 17 SPARQL Jobs in the UK

data ecosystems ( AWS, Azure, GCP ). Strong communication and stakeholder engagement skills — translating complex technical concepts into business outcomes. 💡 Bonus Points For Experience with semantic knowledge graphs , RDF/SPARQL , and ontology/taxonomy modeling . Familiarity with metadata-driven AI/ML enrichment . Knowledge of financial mathematics or capital markets. A “can-do” mindset and hunger for continuous More ❯

data ecosystems ( AWS, Azure, GCP ). Strong communication and stakeholder engagement skills — translating complex technical concepts into business outcomes. 💡 Bonus Points For Experience with semantic knowledge graphs , RDF/SPARQL , and ontology/taxonomy modeling . Familiarity with metadata-driven AI/ML enrichment . Knowledge of financial mathematics or capital markets. A “can-do” mindset and hunger for continuous More ❯

data ecosystems (AWS, Azure, GCP). Strong communication and stakeholder engagement skills — translating complex technical concepts into business outcomes. 💡 Bonus Points For Experience with semantic knowledge graphs , RDF/SPARQL , and ontology/taxonomy modeling . Familiarity with metadata-driven AI/ML enrichment . Knowledge of financial mathematics or capital markets. A “can-do” mindset and hunger for continuous More ❯

data ecosystems (AWS, Azure, GCP). Strong communication and stakeholder engagement skills — translating complex technical concepts into business outcomes. 💡 Bonus Points For Experience with semantic knowledge graphs , RDF/SPARQL , and ontology/taxonomy modeling . Familiarity with metadata-driven AI/ML enrichment . Knowledge of financial mathematics or capital markets. A “can-do” mindset and hunger for continuous More ❯

data ecosystems (AWS, Azure, GCP). Strong communication and stakeholder engagement skills — translating complex technical concepts into business outcomes. 💡 Bonus Points For Experience with semantic knowledge graphs , RDF/SPARQL , and ontology/taxonomy modeling . Familiarity with metadata-driven AI/ML enrichment . Knowledge of financial mathematics or capital markets. A “can-do” mindset and hunger for continuous More ❯

management role Breadth of knowledge and familiarity with metadata, enterprise data modeling and industry best practices Proficiency in Semantic technologies and semantic data modeling including OWL, RDF/S, SPARQL, SHACL, Ontology design and knowledge graphs Experience in semantic model integration into large ecosystems and legacy systems A strong technical or Engineering background and broad technical fluency A track record More ❯

XML, or other structured data formats. Experience with rules engines, decision management systems, or low-code/BPM tools. Understanding of knowledge representation, logic, or semantic technologies (RDF, OWL, SPARQL). Awareness of machine learning and how probabilistic and deterministic reasoning can complement each other. Domain experience in financial services, insurance, healthcare, or other regulated industries. Degree in a logic More ❯

someone who is knowledgeable in a variety of strategies for ingesting, modelling, processing, and persisting data. You are able to use one or more query languages (e.g. SQL, HiveQL, SPARQL), schema definition languages (e.g. DDL, SDL, XSD, RDF), and scripting languages (e.g. Perl, Python, KornShell, Scala) to build a data solution. More ❯

ontology design across domains (assets, 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 prediction, anomaly detection) Optimize graph … 5+ years in engineering, data, or AI 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 engineering literacy (AWS More ❯

ontology design across domains (assets, 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 prediction, anomaly detection) Optimize graph … 5+ years in engineering, data, or AI 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 engineering literacy (AWS More ❯

ontology design across domains (assets, 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 prediction, anomaly detection) Optimize graph … 5+ years in engineering, data, or AI 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 engineering literacy (AWS More ❯

Java and Micro frontend web development with demonstrated ability to write robust, production-quality code. Hands-on experience with knowledge graph and semantic web technologies e.g. RDF, OWL, SHACL, SPARQL Knowledge of one or more rule-based and semantic reasoning tools and frameworks (e.g., Apache Jena, Drools, OWL reasoners such as Pellet or HermiT) Experience working with large-scale data … systems such as Spark, Kafka, or similar. Strong understanding of graph data models and query languages (e.g., SPARQL, Cypher). Excellent communication skills and ability to collaborate across interdisciplinary teams. We'd love to see: Familiarity with knowledge representation and linked data best practices. Understanding of data governance and model change management. Discover what makes Bloomberg unique - watch our for More ❯

rate-limits, auditability. Embed evals & observability; ship via CI/CD. Must-have Shipped knowledge graphs in production (Neo4j/TigerGraph/Neptune or RDF/OWL; Cypher/SPARQL/GSQL ). Delivered GraphRAG with evidence it beats vector-only. Python + LangChain/LlamaIndex; vector stores (Pinecone/Chroma/LanceDB). Cloud delivery (AWS/Azure/… GCP) with basic IaC/CI/CD and governance. Nice-to-have Text-to-Cypher/SPARQL with safety filters and small eval sets. MCP-style tool contracts for safe agent access. Streaming/ELT at scale (Kafka/Databricks/PySpark). More ❯

rate-limits, auditability. Embed evals & observability; ship via CI/CD. Must-have Shipped knowledge graphs in production (Neo4j/TigerGraph/Neptune or RDF/OWL; Cypher/SPARQL/GSQL ). Delivered GraphRAG with evidence it beats vector-only. Python + LangChain/LlamaIndex; vector stores (Pinecone/Chroma/LanceDB). Cloud delivery (AWS/Azure/… GCP) with basic IaC/CI/CD and governance. Nice-to-have Text-to-Cypher/SPARQL with safety filters and small eval sets. MCP-style tool contracts for safe agent access. Streaming/ELT at scale (Kafka/Databricks/PySpark). More ❯

rate-limits, auditability. Embed evals & observability; ship via CI/CD. Must-have Shipped knowledge graphs in production (Neo4j/TigerGraph/Neptune or RDF/OWL; Cypher/SPARQL/GSQL ). Delivered GraphRAG with evidence it beats vector-only. Python + LangChain/LlamaIndex; vector stores (Pinecone/Chroma/LanceDB). Cloud delivery (AWS/Azure/… GCP) with basic IaC/CI/CD and governance. Nice-to-have Text-to-Cypher/SPARQL with safety filters and small eval sets. MCP-style tool contracts for safe agent access. Streaming/ELT at scale (Kafka/Databricks/PySpark). More ❯

rate-limits, auditability. Embed evals & observability; ship via CI/CD. Must-have Shipped knowledge graphs in production (Neo4j/TigerGraph/Neptune or RDF/OWL; Cypher/SPARQL/GSQL ). Delivered GraphRAG with evidence it beats vector-only. Python + LangChain/LlamaIndex; vector stores (Pinecone/Chroma/LanceDB). Cloud delivery (AWS/Azure/… GCP) with basic IaC/CI/CD and governance. Nice-to-have Text-to-Cypher/SPARQL with safety filters and small eval sets. MCP-style tool contracts for safe agent access. Streaming/ELT at scale (Kafka/Databricks/PySpark). More ❯

rate-limits, auditability. Embed evals & observability; ship via CI/CD. Must-have Shipped knowledge graphs in production (Neo4j/TigerGraph/Neptune or RDF/OWL; Cypher/SPARQL/GSQL ). Delivered GraphRAG with evidence it beats vector-only. Python + LangChain/LlamaIndex; vector stores (Pinecone/Chroma/LanceDB). Cloud delivery (AWS/Azure/… GCP) with basic IaC/CI/CD and governance. Nice-to-have Text-to-Cypher/SPARQL with safety filters and small eval sets. MCP-style tool contracts for safe agent access. Streaming/ELT at scale (Kafka/Databricks/PySpark). More ❯