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Sparql Semantic Jobs (NOW HIRING)

Speria

Principal Data Architect

Atlanta, GA · On-site

... SPARQL for semantic interoperability. • Integrate structured and unstructured data into semantic layers for AI and analytics. • Build and optimize high-volume ETL/ELT pipelines using Spark ...

Endurion

Ontologist with Security Clearance

Tampa, FL · On-site

Candidates must have demonstrated expertise in the following areas: • Ontology design and semantic data modeling. • SPARQL query development. • W3C standards (RDF, OWL, SHACL) and supporting ...

Vantor

Ontology Engineer (TS/SCI)

Herndon, VA · On-site

Leveraging Semantic Web standards, including RDF, OWL, and SPARQL, the Lead Ontologist develops scalable knowledge frameworks that enhance data discoverability, support AI/ML applications, and ...

Vantor

Ontology Engineer (TS/SCI)

Herndon, VA · On-site

$137K - $200K/yr

Leveraging Semantic Web standards, including RDF, OWL, and SPARQL, the Lead Ontologist develops scalable knowledge frameworks that enhance data discoverability, support AI/ML applications, and ...

CELESTAR

Lead Ontologist - OBIQUA

Reston, VA · On-site

... semantic web standards (e.g., RDF, OWL, SPARQL) and government data standards to enable semantic representation of data inputs, facilitating integration and interoperability across intelligence ...

Evolutyz Corp

Principal Data Architect

Houston, TX · On-site

Mastery of semantic web standards, including RDF, OWL, and SHACL, and proficiency in SPARQL for context-aware graph reasoning. • Policy-as-Code Compliance: Production-grade deployment experience ...

Allstate

Senior AI Engineer

Chicago, IL · On-site

$126K - $166K/yr

In this role, you will design and implement agent‑driven pipelines that leverage RDF/OWL ontologies, SPARQL, and Large Language Models (LLMs) to perform semantic alignment, dimension mining, and ...

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Sparql Semantic information

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$120.5K

$162.4K

$187.5K

How much do sparql semantic jobs pay per year?

As of Sep 4, 2026, the average yearly pay for sparql semantic in the United States is $162,359.00, according to ZipRecruiter salary data. Most workers in this role earn between $151,000.00 and $176,000.00 per year, depending on experience, location, and employer.

What is a sparql semantic job?

SPARQL Semantic jobs involve working with SPARQL, the query language used to retrieve and manipulate data stored in Resource Description Framework (RDF) format within semantic web technologies. Professionals in these roles design, write, and optimize SPARQL queries to extract meaningful insights from linked data and knowledge graphs. They often collaborate with data scientists, knowledge engineers, and software developers to implement semantic data solutions in areas like data integration, artificial intelligence, and enterprise knowledge management.

What are the common challenges faced by professionals working with SPARQL and semantic web technologies?

Professionals in SPARQL and semantic web roles often encounter challenges such as integrating heterogeneous data sources, ensuring data quality and consistency, and optimizing complex queries for performance. Working with RDF data models requires a solid understanding of ontologies and linked data principles, which can be a learning curve for those new to semantic technologies. Collaboration with data architects, domain experts, and software engineers is essential, as projects typically involve cross-functional teams to model, curate, and extract meaningful insights from large and diverse datasets.

What are the key skills and qualifications needed to thrive as a sparql semantic developer, and why are they important?

To thrive as a SPARQL Semantic Developer, you need expertise in semantic web technologies, RDF data modeling, and strong proficiency in SPARQL query language, often supported by a background in computer science or information science. Familiarity with tools like Apache Jena, Virtuoso, and ontology editors such as Protégé, as well as knowledge of related standards like OWL and SHACL, is typically required. Critical thinking, attention to detail, and effective problem-solving are vital soft skills for designing scalable data solutions and collaborating with cross-functional teams. These skills are crucial for building robust semantic applications that enable meaningful data integration, discovery, and analysis across diverse systems.

What is the difference between Sparql Semantic vs Data Analyst?

AspectSparql SemanticData Analyst
Required CredentialsKnowledge of SPARQL, semantic web technologies, RDF, ontologiesDegree in statistics, data science, or related field; proficiency in SQL and data visualization tools
Work EnvironmentSemantic web projects, knowledge graphs, linked data environmentsBusiness intelligence, data reporting, analytics teams
Employer & Industry UsageResearch institutions, semantic web companies, data integration projectsCorporations, marketing firms, finance, healthcare
Common Search & ComparisonUnderstanding semantic data queryingAnalyzing and interpreting data for decision-making

While Sparql Semantic specialists focus on querying and managing semantic web data using SPARQL, Data Analysts interpret and analyze data to support business decisions. Both roles require data literacy but differ in technical skills and work environments.

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Sparql Semantic jobs near you
Infographic showing various Sparql Semantic job openings in the United States as of August 2026, with employment types broken down into 90% Full Time, 5% Part Time, and 5% Contract. Highlights an 73% Physical, 6% Hybrid, and 21% Remote job distribution, with an average salary of $162,359 per year, or $78.1 per hour.

Data Science / Knowledge Graph Engineer

VeeRteq Solutions Inc.

Chicago, IL • On-site

$118K - $141K/yr

Contractor

This job post has expired 3 days ago. Applications are no longer accepted.

Job description

Job Description

Job Title: Data Science / Knowledge Graph Engineer

Location: Chicago, IL
 

Job Summary

We are seeking a skilled Data Science / Knowledge Graph Engineer with hands-on experience in semantic modeling, knowledge graphs, graph databases, and data transformation. The ideal candidate will have experience working with platforms such as Stardog, Neo4j, GraphDB, or similar technologies, along with strong SQL and data analysis skills.

The role will focus on understanding domain data and business relationships, designing semantic models and ontologies, building and maintaining knowledge graphs, and developing graph-based data solutions. The resource will collaborate closely with data engineers, architects, domain teams, and AI engineers.

Key Responsibilities
  • Understand domain data and business relationships.
  • Design semantic models and ontologies.
  • Build and maintain knowledge graphs.
  • Create source-to-graph mappings and hydrate graphs with data.
  • Develop RDF, OWL, SHACL, and SPARQL queries.
  • Validate data quality and troubleshoot graph-related issues.
  • Perform data transformation and mapping activities required for graph solutions.
  • Work with data engineers, architects, domain teams, and AI engineers to support knowledge graph initiatives.
  • Analyze data and ensure the quality and consistency of graph-related data.
  • Support the development and maintenance of semantic data models and knowledge graph solutions.
Required Experience
  • Hands-on experience with Stardog, Neo4j, GraphDB, or similar graph database/platform technologies.
  • Strong knowledge of semantic modeling.
  • Strong understanding of knowledge graphs.
  • Experience with RDF.
  • Experience with SPARQL.
  • Experience with semantic models and ontologies.
  • Experience with data transformation, mapping, and graph hydration.
  • Strong SQL skills.
  • Strong data analysis skills.
  • Experience validating data quality and troubleshooting graph-related issues.
Preferred Experience
  • Experience with Azure Databricks or similar data platforms.
  • Experience working with data engineering teams and enterprise data platforms.
  • Experience collaborating with AI engineers and architecture teams.