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Sparql Semantic Jobs (NOW HIRING)

Senior Semantic Web Engineer (Hybrid)

Chicago, IL · On-site

$126K - $166K/yr

Position:- Senior Semantic Web Engineer Location:- Chicago, IL (Hybrid) Contract WHAT YOU'LL DO ... Practical experience with RDF, OWL, SPARQL, and ideally SHACL. * Experience with relational ...

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

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 ...

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)

... 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 ...

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

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 ...

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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 23, 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:
Infographic showing various Sparql Semantic job openings in the United States as of July 2026, with employment types broken down into 88% Full Time, 8% Part Time, and 4% Contract. Highlights an 72% Physical, 5% Hybrid, and 23% Remote job distribution, with an average salary of $162,359 per year, or $78.1 per hour.

Senior Semantic Web Engineer (Hybrid)

SR Partners LLC

Chicago, IL • On-site

$126K - $166K/yr

Other

Posted 3 days ago


Job description

Position:- Senior Semantic Web Engineer

Location:- Chicago, IL (Hybrid)

Contract

Job description

WHAT YOU'LL DO:

  • Serve as a subject matter expert in semantic web development on our graph data team, contributing to initiatives that integrate AI, LLMs, and advanced graph technologies.
  • Collaborate with the Staff Semantic Engineer and other senior engineers to standardize tooling, design patterns, and modeling approaches.
  • Help define the technical direction for core semantic capabilities, ensuring scalable and robust solutions.
  • Independently research, evaluate, and propose innovative solutions to complex and ambiguous technical challenges.
  • Build and manage scalable knowledge graph solutions, including data ingestion, linking, and querying mechanisms.
  • Write, test, and document clean, maintainable code, and apply automation to testing, integration, and deployment processes.
  • Partner with product owners to refine features into actionable user stories that deliver business value.
  • Evaluate and recommend external taxonomies and ontologies; author new ones as needed to support our domain.
  • Recommend and implement semantic web tools, platforms, and technologies.
  • Support ontology governance processes and enterprise graph management tools.
  • Collaborate with stakeholders, including data scientists, engineers, and developers, to understand requirements and build effective semantic solutions.
  • Provide technical mentorship to junior team members on semantic web principles and implementation patterns.

WHAT YOU'LL NEED:

  • Bachelor's or Master's degree in Computer Science, Information Technology, or a related STEM field
  • 5+ years of hands-on experience in semantic web or knowledge graph engineering, including leading complex projects.
  • Proven experience with graph databases or triple stores such as Amazon Neptune, Neo4j, Virtuoso, or GraphDB. (Amazon Neptune preferred)
  • Strong proficiency in Python; familiarity with other languages (e.g., Java, C#, JavaScript, Clojure) is a plus.
  • Practical experience with RDF, OWL, SPARQL, and ideally SHACL.
  • Experience with relational databases (SQL) and graph databases (SPARQL).
  • Hands-on experience with ontology/graph tools such as Prot g , TopBraid, or Metaphactory. (Metaphactory preferred)
  • Solid understanding of data modeling, ETL processes, and data governance.
  • Experience with cloud platforms (AWS preferred) and their data services.
  • Understanding of AI/ML concepts and how semantic data can enhance AI applications.
  • Familiarity with CI/CD, agile practices, and infrastructure tools like Git, Jenkins, Azure DevOps, and Terraform.
  • Strong communication and problem-solving skills, with the ability to explain complex technical concepts to non-technical stakeholders.
  • Bonus: Understanding of healthcare ontologies and standards like SNOMED-CT, LOINC, RxNorm, and ICD-10

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