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How much do manager knowledge graph jobs pay per hour?

As of Sep 13, 2026, the average hourly pay for manager knowledge graph in the United States is $26.35, according to ZipRecruiter salary data. Most workers in this role earn between $17.31 and $32.69 per hour, depending on experience, location, and employer.

What is the difference between Manager Knowledge Graph vs Data Analyst?

AspectManager Knowledge GraphData Analyst
Required CredentialsBachelor's degree in Computer Science, Data Science, or related field; knowledge of graph databasesBachelor's degree in Statistics, Mathematics, or related field; proficiency in data analysis tools
Work EnvironmentCollaborative teams, often in tech or data-driven companiesOffice setting, analyzing data sets, creating reports
Industry UsageUsed in AI, semantic web, knowledge management projectsUsed across finance, marketing, healthcare for data insights

The Manager Knowledge Graph focuses on designing and managing knowledge graph systems, requiring expertise in graph databases and data modeling. Data Analysts primarily interpret data to generate insights, using statistical tools. While both roles work with data, the Manager Knowledge Graph is more technical and system-oriented, whereas Data Analysts focus on data interpretation and reporting.

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Manager Knowledge Graph jobs near you

Ontology / Knowledge Graph Engineer

Montclair, NJ • On-site

2T Consulting
IT Services • 51 - 200 employees
Learn more about 2T Consultingexternal

Full-time

Posted 8 days ago

Job description

We are seeking an experienced Ontology / Knowledge Graph Engineer with strong expertise in ontology engineering, semantic modeling, and knowledge graph development. The ideal candidate will have hands-on experience designing and implementing ontology-driven knowledge graphs using standards such as OWL, RDF, SPARQL, SHACL, and JSON-LD.

Required Skills
  • Strong experience in Ontology Engineering and ontology-driven knowledge graph design.
  • Expertise in Knowledge Modeling and Semantic Modeling.
  • Hands-on experience with OWL, RDF, SPARQL, SHACL, and JSON-LD.
  • Experience with Ontological Inference and consistency checking.
  • Strong knowledge of Knowledge Graphs, RDF Graphs, and Property Graphs.
  • Experience with Graph Data Modeling and Graph Analytics.
  • Hands-on experience with Entity Resolution.
  • Ability to design and implement scalable semantic and knowledge graph solutions.
Technologies / Tools
  • Protégé
  • TopBraid Composer
  • OntoStudio
  • Neo4j
  • Stardog
  • GraphDB
  • Apache Jena
  • Fuseki
  • Blazegraph
  • Virtuoso
Key Responsibilities
  • Design, develop, and maintain enterprise ontologies and semantic models.
  • Build ontology-driven Knowledge Graph (KG) solutions aligned with business and technical requirements.
  • Develop and manage RDF-based knowledge graphs using OWL, RDF, SPARQL, SHACL, and JSON-LD.
  • Implement ontological inference and reasoning capabilities.
  • Perform consistency checking and validation of ontologies and knowledge graph data.
  • Develop graph data models and support both RDF and property graph architectures.
  • Implement entity resolution and semantic relationships across disparate data sources.
  • Perform graph analytics to derive insights from connected data.
  • Use ontology and knowledge graph tools such as Protégé, TopBraid Composer, Stardog, GraphDB, Neo4j, and Apache Jena.
  • Collaborate with data engineers, architects, and business stakeholders to define semantic requirements and modeling standards.
  • Establish best practices for ontology governance, versioning, validation, and knowledge graph quality.

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