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Sparql Semantic Jobs (NOW HIRING)

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 ...

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 ...

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)

Maxar

$115K - $151K/yr

Leveraging Semantic Web standards, including RDF, OWL, and SPARQL, the LeadOntologistdevelops 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 ...

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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 Jul 3, 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
What cities are hiring for Sparql Semantic jobs? Cities with the most Sparql Semantic job openings:
What states have the most Sparql Semantic jobs? States with the most job openings for Sparql Semantic jobs include:
What job categories do people searching Sparql Semantic jobs look for? The top searched job categories for Sparql Semantic jobs are:
Sparql Semantic jobs near you
Infographic showing various Sparql Semantic job openings in the United States as of June 2026, with employment types broken down into 89% Full Time, 7% Part Time, and 4% Contract. Highlights an 69% Physical, 8% Hybrid, and 23% Remote job distribution, with an average salary of $162,359 per year, or $78.1 per hour.
Ontologist/Semantic Data Architect : Bristol-Myers Squibb

Ontologist/Semantic Data Architect : Bristol-Myers Squibb

ShiftCode Analytics

Lawrence Township, NJ • On-site

Other

Posted 15 days ago

Job description

Ontologist/Semantic Data Architect

This role involves FAIRification of data and is part of the FAIR Data Services team. This role is responsible for defining opportunities to standardize common business and scientific vocabularies, and to convert both legacy and new datasets into semantically enriched data assets.

As a member of the Semantic Data Engineering Team, you will support the translation of both legacy and new datasets into semantically enabled data models. Your responsibilities will include making Client research data more Findable, Accessible, Interoperable, and Reusable. Following the evaluation of existing business related process and data, development of semantic ontologies and taxonomies will be developed and used to both graph and harmonize research data. Opportunities to standardize existing vocabularies will be defined, and sematic vocabularities created. You will develop methods for providing access to these semantic data products through queries, APIs, and other programmatic means. In this role, you will collaborate with business partners, subject matter experts and engineering teams.

Technical/functional Skills:

  • Experience working in a life sciences or biopharmaceutical environment such as early-stage research, drug discovery, or other biological sciences discipline is preferred.
  • Familiarity with data engineering patterns and pipeline tools and processes including SQL vs NoSQL, GRAPHQL, SPARQL, ETL, Data Warehousing, Protégé, GraphQL, DataOps, TopBraid EDG, Centree, Termite.
  • Able to present your work, both verbally and in writing, to diverse audiences including scientific stakeholders, technical teams, as well as research leadership.
  • Able to effectively lead, manage, inspire, and influence globally distributed and cross-functional teams.
  • Experience working in an agile software development environment
  • Experience in representing and expressing information models (conceptual, logical, entities and their relationships), use of tools such as ER Studio to author such models.
  • Experience in interpreting and translating Information models (conceptual and logical) to their equivalent semantic models (OWL, RDF etc.) using tools such as Top Braid, Protégé etc.

Experience:

  • 5 years of experience with ontologies, taxonomies, RDF/OWL, SHACL, SPARQL, Knowledge Graphs, and related tools
  • 3-5 years data architecture experience
  • 3-5 years of experience in data quality management
  • 3-5 years of experience in metadata management
  • Experience with graph databases (neo4j, AnzoGraph, Amazon Neptune)
  • Experience with taxonomy and ontology development tools and industry standard knowledge graph database tooling
  • Experience in developing mappings and transformation processes to take data from a relational paradigm into a knowledge graph environment
  • Experience utilizing graph data in a machine learning environment
  • Working knowledge of databases, MDM, RDM, warehousing architecture, dimensional modelling, design patterns and strategy
  • Experience collaborating with cross functional teams
  • Must be proactive and self-driven, demonstrated initiative and be a logical thinker.
  • Strong leadership, communication, collaboration skills with a track record of taking solution ownership
ShiftCode Analytics logo

About ShiftCode Analytics

Sourced by ZipRecruiter

We specialize in solid end-to-end delivery of tailor-made technology solutions designed by the Top 1% Software Engineering teams. Our innate digital leadership identity powers transformation across every industry. We are always ready to drive meaningful change with a strategic vision for the future. We rigorously test for logical/mathematical reasoning skills, technical ability and soft skills in our interview process. Only those engineers who score highly across each of these areas are presented to our clients.

Industry

It services

Company size

11 - 50 Employees

Headquarters location

Tampa, FL, US

Year founded

2019

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