21 of 21 SPARQL Jobs

maintaining them AWS Specialty Certification - Machine Learning AWS Foundational Certification - AI Practitioner Prior experience working with healthcare data Exposure to knowledge graph-related technologies and standards (Graph DB, OWL, SPARQL) $131,000 - $181,000 a year Compensation at IMO Health is determined by job level, role requirements, and each candidate's experience, skills, and location. The listed base pay represents More ❯

Ontology (BFO) and the Common Core Ontologies (CCO) or similar tool Experience using the ontology editor Protégé or similar tool Familiarity with the Web Ontology Language (OWL) and the SPARQL query language or similar tool Experience using GraphDB or similar knowledge graph tool Experience developing Python scripts Experience with databases Experience using knowledge graphs Lastly, as we are working for More ❯

H2O, or similar Experience with LLM Agents, Agentic programming Experience with search architecture (for instance: Solr, ElasticSearch, AWS OpenSearch) Experience with building querying ontologies such as Zeno, OWL, RDF, SparQL or comparable are preferred Knowledge & experience with microservices, service mesh, API development and test automation are preferred Demonstrated experience using Docker, Kubernetes, and/or other similar container frameworks are More ❯

H2O, or similar Experience with LLM Agents, Agentic programming Experience with search architecture (for instance: Solr, ElasticSearch, AWS OpenSearch) Experience with building querying ontologies such as Zeno, OWL, RDF, SparQL or comparable are preferred Knowledge & experience with microservices, service mesh, API development and test automation are preferred Demonstrated experience using Docker, Kubernetes, and/or other similar container frameworks are More ❯

Experience with programming in TensorFlow, PyTorch Experience with Hadoop, MapReduce Experience with Tableau Experience with Cognos Experience with designing, implementing, and using REST APIs Experience with RDF/OWL, SPARQL, and Semantic Web technologies Experience with Statistical and ML analytics and modeling (e.g., R, Spark, etc.) or other deep learning frameworks a plus Experience with Data catalogs and data management More ❯

Experience with programming in TensorFlow, PyTorch Experience with Hadoop, MapReduce Experience with Tableau Experience with Cognos Experience with designing, implementing, and using REST APIs Experience with RDF/OWL, SPARQL, and Semantic Web technologies Experience with Statistical and ML analytics and modeling (e.g., R, Spark, etc.) or other deep learning frameworks a plus Experience with Data catalogs and data management More ❯

tooling. Excited to mentor others, set high standards, and drive alignment across a multidisciplinary team. Bonus points if you have: Experience with knowledge graph technologies (e.g., Neo4j, RDF/SPARQL, Cypher). Experience with healthcare and life sciences ontologies such as Mondo, OMOP, FHIR, SNOMED, RxNorm, UMLS . Experience harmonizing datasets from EHR, claims, or biomedical research domains. Contributions to 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 ❯

USD, gITF, etc) Interest in digital twins: Interest in becoming a technical and industry expert in digital twins It's helpful to have Experience with: Semantic modeling (RDF, OWL, SPARQL) Differentiable programming Numerical methods and graph computing Swift programming language Building science fundamentals: A fundamental understanding of building energy, HVAC systems, and/or electromechanical systems. Knowledge of current semantic More ❯

years' experience or training in ontology and linked data tools (Protégé, TopQuadrant, PoolParty, Stardog, AnzoGraph, Neptune, or Data.World) At least 3 years' experience or training with SQL or SPARQL Preferred Qualifications Master's degree in information science, computer science, engineering, library science, ontology, semantics or computational linguistics Understanding of the development of ontologies and the use of controlled vocabularies and More ❯

years' experience or training in ontology and linked data tools (Protégé, TopQuadrant, PoolParty, Stardog, AnzoGraph, Neptune, or Data.World) At least 3 years' experience or training with SQL or SPARQL Preferred Qualifications Master's degree in information science, computer science, engineering, library science, ontology, semantics or computational linguistics Understanding of the development of ontologies and the use of controlled vocabularies and More ❯

years' experience or training in ontology and linked data tools (Protégé, TopQuadrant, PoolParty, Stardog, AnzoGraph, Neptune, or Data.World) At least 3 years' experience or training with SQL or SPARQL Preferred Qualifications Master's degree in information science, computer science, engineering, library science, ontology, semantics or computational linguistics Understanding of the development of ontologies and the use of controlled vocabularies and More ❯

years' experience or training in ontology and linked data tools (Protégé, TopQuadrant, PoolParty, Stardog, AnzoGraph, Neptune, or Data.World) At least 3 years' experience or training with SQL or SPARQL Preferred Qualifications Master's degree in information science, computer science, engineering, library science, ontology, semantics or computational linguistics Understanding of the development of ontologies and the use of controlled vocabularies and More ❯

years' experience or training in ontology and linked data tools (Protégé, TopQuadrant, PoolParty, Stardog, AnzoGraph, Neptune, or Data.World) At least 3 years' experience or training with SQL or SPARQL Preferred Qualifications Master's degree in information science, computer science, engineering, library science, ontology, semantics or computational linguistics Understanding of the development of ontologies and the use of controlled vocabularies and More ❯

graphs/graph databases (Neo4j preferred). Expertise with tuning and scaling Graph databases (Neo4j preferred). Expertise with graph data models (LPG, RDF) and graph languages (Cypher, Gremlin, SparQL) with hands-on graph data modeling techniques for common use cases. Experience with graph data modeling, graph schema development, graph data design. 4+ years experience developing graph algorithms, optimizing complex 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 ❯

Your responsibilities will include: Design, implement, and maintain ETL pipelines to prepare data for graph-based structures. Develop and optimize graph database solutions using querying languages such as Cypher, SPARQL, or GQL. Neo4J DB experience is preferred. Build and maintain ontologies and knowledge graphs, ensuring efficient and scalable data modeling. Integrate vector databases and implement similarity search techniques, with a … With 3 years of experience working with Graph DB. Engineering experience within AWS systems is highly preferred Programming: Proficiency in Python and PySpark programming. Querying: Advanced knowledge of Cypher, SPARQL, or GQL querying languages. ETL Processes: Expertise in designing and optimizing ETL processes for graph structures. Data Modeling: Strong skills in creating ontologies and knowledge graphs. Presenting data for Graph More ❯

Design and develop a scalable modular semantic layer framework, which can be seamlessly integrated with various data and artificial intelligence (AI) and machine learning (ML) components across the organization. Create logical and physical data models, ensuring data consistency, integrity, and 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 ❯