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How much do graph jobs pay per hour?

As of Sep 14, 2026, the average hourly pay for graph in the United States is $31.03, according to ZipRecruiter salary data. Most workers in this role earn between $15.87 and $25.96 per hour, depending on experience, location, and employer.

What is a graph?

A Graph job typically refers to a position involving the analysis, visualization, or implementation of graph-based data structures and algorithms. This may include working with graph databases, network analysis, or machine learning applications that leverage graph theory. Common roles include Graph Data Scientist, Graph Engineer, or Network Analyst, often requiring expertise in tools like Neo4j, GraphQL, or NetworkX. These jobs are commonly found in industries such as social networks, cybersecurity, recommendation systems, and logistics.

How does a graph database engineer typically collaborate with data scientists and software developers in a project setting?

Graph Database Engineers often work closely with data scientists to design and optimize data models that support complex relationships and queries. They collaborate with software developers to integrate graph databases into applications, ensuring seamless data flow and performance. Regular meetings and code reviews help align database structures with business requirements and analytical goals. This cross-functional teamwork is essential for delivering scalable, high-performing solutions that leverage graph-based data.

What are the key skills and qualifications needed to thrive as a graphic designer, and why are they important?

To thrive as a Graphic Designer, you need a strong foundation in design principles, creativity, and proficiency in visual communication, often supported by a degree in graphic design or a related field. Mastery of technical tools such as Adobe Creative Suite (Photoshop, Illustrator, InDesign) and knowledge of digital asset management systems are typically required. Excellent communication, time management, and collaboration skills help designers effectively convey ideas and work with clients or teams. These skills are essential to producing compelling visuals that meet client goals and stand out in a competitive creative industry.

What is the difference between Graph vs Data Analyst?

AspectGraphData Analyst
Required CredentialsTypically no formal degree, but knowledge of graph theory helpsBachelor's or higher in data science, statistics, or related fields
Work EnvironmentResearch, academia, or specialized tech rolesBusiness, finance, healthcare, and various industries
Employer & Industry UsageUsed in computer science, mathematics, and research projectsApplied in analyzing data trends, reporting, and decision-making

While a graph refers to a mathematical or visual representation of data, a Data Analyst is a professional who interprets data, often using graphs as tools. The Data Analyst's role involves analyzing data sets, creating visualizations, and providing insights, whereas a graph is a component or tool used within data analysis processes.

What careers use graphs?

Careers that use graphs include data analysts, statisticians, data scientists, and business analysts, who interpret and visualize data to support decision-making. These roles often require skills in data visualization tools like Excel, Tableau, or Power BI, and involve analyzing trends, patterns, and relationships within data sets.
More about Graph jobs

What cities are hiring for Graph jobs?

Cities with the most Graph job openings:

What states have the most Graph jobs?

States with the most job openings for Graph jobs include:

What job categories do people searching Graph jobs look for?

The top searched job categories for Graph jobs are:

What other helpful pages are available for Graph?

Other pages related to Graph:

Graph jobs near you
Infographic showing various Graph job openings in the United States as of September 2026, with employment types broken down into 66% Full Time, 17% Part Time, and 17% Contract. Highlights an 100% In-person job distribution, with an average salary of $64,550 per year, or $31 per hour.

Ontology / Knowledge Graph Engineer

Carteret, NJ • On-site

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

Full-time

Posted 9 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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