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Sparql Semantic Jobs (NOW HIRING)

Swift Hire LLC

Principal Data Architect

Menlo Park, CA · Remote

Advanced Semantic Engineering: Comprehensive mastery of semantic web standards, including RDF, OWL, and SHACL, for building ontology-first structural data models alongside SPARQL for context-aware ...

Vizient

Senior Ontology and Knowledge Engineer

Irving, TX · On-site

$102K - $179K/yr

Support knowledge graph development and integration with enterprise data platforms, including semantic-to-data mapping, graph and triplestore implementation, and SPARQL query development. * Perform ...

Vizient

Senior Ontology and Knowledge Engineer

Chicago, IL · On-site

$102K - $179K/yr

Support knowledge graph development and integration with enterprise data platforms, including semantic-to-data mapping, graph and triplestore implementation, and SPARQL query development. * Perform ...

SOSi

Ontologist

$117K - $140K/yr

OR a minimum of 11+ years of experience in ontology development, semantic technologies. * Possess the knowledge and capability to develop ontologies: * Proficiency in writing advanced SPARQL queries.

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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.

More about Sparql Semantic jobs

What cities are hiring for Sparql Semantic jobs?

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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.

Principal Data Architect

Swift Hire LLC

Menlo Park, CA • Remote

Contractor

Posted 9 days ago

Job description

Principal Data Architect

Location: Menlo Park, CA(Remote) 

Position Overview: We are looking for a forward thinking 10+ Years Data Architect, who is visionary to pioneer the engineering and orchestration of an enterprise-scale, Self-Healing Data Fabric. In this high-impact mandate, you will dismantle traditional, rigid ETL pathways and help implement an intelligent "nervous system" framework where operational metadata is continuously active, enterprise data governance is completely computational, and multi-party data virtualization relies on zero-copy architectures. Mandatory Technical: • Active Metadata Infrastructure: Demonstrated success designing closed-loop data automation pipelines (e.g., building automated engines for metadata-triggered schema self-repair and structural drift remediation). • Advanced Semantic Engineering: Comprehensive mastery of semantic web standards, including RDF, OWL, and SHACL, for building ontology-first structural data models alongside SPARQL for context-aware graph reasoning. • Policy-as-Code Compliance: Production-grade deployment experience utilizing Open Policy Agent (OPA) or equivalent zero-trust policy engines to enforce programmatic, contextual data access control layers. • Caelum or Amundsen push-events: Alongside DataHub's Actions Framework to drive real-time, event-based data quality orchestration and automated schema rollbacks

Note: 

Target Educational Profiles: • Required: Minimum of 10+ years of enterprise data strategy experience. • Preferred: Master's degree or Ph.D. in Computer Science with a core focus on Formal Methods/Symbolic Logic or Computational Mathematics. • Key Focus Areas: Active Metadata, RDF, OWL, SHACL, SPARQL, OPA, Caelum/Amundsen.