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Sparql Semantic Jobs (NOW HIRING)

TetraScience

Data & Semantic Model Architect

$65.25 - $84/hr

Deep, hands-on expertise with semantic web standards (RDF, OWL, SHACL, SPARQL) and property graph concepts (LPG). Requirements * 7+ years of experience in data architecture, informatics, or technical ...

Programmers.io

Ontology Business Consultant

Tampa, FL · On-site

Ontologist, Ontology Engineer, Semantic Data Modeler, Knowledge Graph Engineer, Semantic Modeler Lead, Ontology Consultant. • Tech stack: RDF, OWL, SHACL, SPARQL, Stardog (or GraphDB, Blazegraph ...

Quiet Professionals LLC

Ontologist

Tampa, FL · On-site

$108K - $129K/yr

Ontology design and semantic data modeling. * SPARQL query development. * W3C standards (RDF, OWL, SHACL) and supporting frameworks like Basic Formal Ontology (BFO) and Common Core Ontologies (CCO)

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Sparql Semantic information

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$120.5K

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$187.5K

How much do sparql semantic jobs pay per year?

As of Jun 9, 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 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.

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 SPARQL Semantic jobs?

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.
More about Sparql Semantic jobs
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Sparql Semantic jobs near you

Semantic Software Engineer [77379]

Skyelia

Louisville, TN • On-site, Remote

Other

Posted 10 days ago

Job description

About:
  • Contract: 6+ months
  • Location: Louisville, TN
Qualifications:
  • Experience Required: 8-10
  • 7+ years as Semantic Software Engineer
  • Data Virtualization - 7+ years
  • Experienced Semantic Software Engineer to design and develop software solutions that leverage semantic technologies, ontologies, and structured knowledge models.
  • The role focuses on enabling semantic interoperability, knowledge-driven applications, and standards-based data exchange across enterprise platforms.
  • Practical experience implementing semantic data virtualization (e.g. R2RML mappings) and integrating knowledge graphs with analytics pipelines.
  • Proficiency with semantic stores reasoners and building scalable SPARQL GraphQL or API based semantic services.
Roles & Responsibilities:
  • Design and develop semantic-enabled software components and services
  • Implement solutions that leverage ontologies, knowledge models, and semantic metadata
  • Integrate semantic layers with APIs, backend services, and data platforms
  • Develop and maintain semantic data processing and validation logic
  • Collaborate with ontologists, architects, and domain experts to translate semantic models into cutable solutions
  • Support semantic interoperability across systems and platforms
  • Ensure semantic consistency across data ingestion, transformation, and consumption layers
  • Participate in design reviews, code reviews, and architecture discussions
  • Troubleshoot and resolve issues related to semantic data interpretation and integration
  • Follow software engineering best practices for coding, testing, and documentation
  • Strong understanding of software development principles and SDLC
  • Hands-on experience working with structured data models and metadata-driven systems
  • Experience integrating semantic models with backend services or APIs
  • Familiarity with ontology-driven or standards-based data representations
  • Strong problem-solving, analytical, and debugging skills
  • Ability to collaborate with both technical and domain stakeholders
  • Experience working in agile development projects and sprint deliver
Must Have:
  • Minimum 7-10 years of experience as a Semantic Software Engineer
  • Practical, hands-on experience implementing semantic data virtualization, including R2RML mappings
  • Experience integrating knowledge graphs with analytics pipelines
  • Proficiency with semantic stores, reasoners, and building scalable SPARQL, GraphQL, or API-based semantic services
  • Experience integrating semantic models with backend services or APIs within metadata-driven or ontology-driven systems

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