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Sparql Semantic Jobs (NOW HIRING)

Allstate

Senior AI Engineer

Chicago, IL

$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 ...

Nalley Consulting

Ontologist - Sr

Miami, FL · On-site

$117K - $154K/yr

Candidates should have demonstrated expertise in ontology design, semantic data modeling, and SPARQL query development, with proficiency in W3C standards (RDF, OWL, SHACL) and supporting frameworks ...

Nalley Consulting

Ontologist - Sr

Doral, FL · On-site

$117K - $154K/yr

Candidates should have demonstrated expertise in ontology design, semantic data modeling, and SPARQL query development, with proficiency in W3C standards (RDF, OWL, SHACL) and supporting frameworks ...

SOSi

Ontologist-WO-007

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.

TSC

Senior AI Engineer

Dahlgren, VA · On-site

$106K - $146K/yr

Responsibilities : • Design, develop, and maintain formal ontologies using OWL, RDF/RDFS, and SPARQL aligned with DoD mission engineering requirements and semantic interoperability standards. • ...

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 Jun 8, 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 Data and AI Engineer

Semantic Data and AI Engineer

Enterprise Knowledge

Arlington, VA • On-site, Remote

$131K - $158K/yr

Full-time

Posted 21 days ago

Job description

Enterprise Knowledge (EK) is hiring for a full-time Semantic Data and AI Engineer to join our growing Knowledge and Data Services Sector. In this role, you will be responsible for designing and deploying cutting-edge data discovery, integration, and governance solutions for a wide range of organizations around the world. The Semantic Data and AI Engineer will be part of a team working on innovative projects and developing orchestrated data solutions to integrate, enrich, and transform a range of knowledge assets (structured and unstructured) for Artificial Intelligence (AI) solutions. This individual will be able to quickly learn new technologies and apply them to business challenges at large corporations, organizations, and federal agencies. The right candidate will have a passion for working with diverse data types and applying new methods and approaches to data challenges with a strategic mindset to advise clients on enterprise AI transformations.
As an EK Semantic Data and AI Engineer, you will join a fast-growing company that is committed to equity and inclusion, have the opportunity to work in a collaborative workplace, take advantage of our unique benefits, and help build our innovative culture. To read more about the impactful work we are doing and to see the latest thought leadership from EK, follow us on LinkedIn.
Responsibilities
  • Work with data subject matter experts and business users to effectively understand and model their domain of knowledge
  • Apply NLP techniques (entity extraction, classification, and document processing) to transform raw data and content into AI-ready assets
  • Design, implement, test, and operate end-to-end RAG workflows for client engagements, including retrieval pipeline architecture, embedding strategies, and response evaluation
  • Contribute to agentic AI solution design and implementation, including orchestration patterns, tool use, and memory and retrieval integration
  • Support a variety of business intelligence projects using AI-based solutions
  • Analyze complex datasets and communicate insights to both technical and non-technical stakeholders
  • Design and implement data pipelines for ingesting, processing, and enriching structured and unstructured content using SQL, Python, R, or equivalent languages
  • Contribute to semantic layer and knowledge graph implementations as part of larger AI solution architectures
  • Work with internal and external teams to contextualize data engineering work into larger project context

Requirements
As a federal contractor, Enterprise Knowledge will not sponsor a new applicant for employment authorization, or offer any immigration related support for this position (i.e. H1B, F-1 OPT, F-1 STEM OPT, F-1 CPT, J-1, TN, E-2, E-3, L-1 and O-1, or any EADs or other forms of work authorization that require immigration support from an employer.
Our office is located in Arlington, VA, and operates on a hybrid model. While local candidates are preferred, we are also able to hire remote candidates residing in the following states: CO, FL, MA, NC, NH, NM, NY, OR, PA, RI, TX, and WA.
Required Skills and Qualifications:
  • Bachelor's degree in math, statistics, economics, data science, computer science, or a related field
  • 5+ years experience working on data analysis project(s) designing reports and designing data analysis approaches and visualizations in a production setting
  • Proven experience working directly with clients, providing briefings, facilitating meetings, and presenting work products
  • Experience applying machine learning methods and statistical analysis to business use cases
  • Proficiency in programming languages such as Python, R, or similar for data analysis and modeling
  • Experience with NLP methods: entity extraction, text classification, document processing, or similar techniques applied to unstructured data in a production setting
  • Hands-on experience building and optimizing RAG pipelines, including embedding strategies, reranking, and cross-encoder models
  • Familiarity with retrieval quality and evaluation metrics (precision, recall, MRR, and user-centric evaluation approaches)
  • Experience implementing monitoring and observability for RAG and AI components, including latency, success rate, cache hit rate, retrieval quality, and data drift
  • Familiarity with data modeling, database architecture, and data integration, aggregation and normalization across heterogeneous sources
  • Interest in developing as a consultant and taking on additional responsibilities for delivering and growing work
Preferred Skills and Qualifications:
  • Experience designing and working with relational databases
  • Experience designing and working with graph databases and SPARQL
  • Experience with AI governance practices covering model monitoring, evaluation frameworks, and access entitlements
  • Comfortable working with containerized environments; Docker proficiency expected, Kubernetes familiarity a plus
  • Experience with cloud platforms (AWS, Azure, or GCP) for deploying and operating AI and data solutions
  • Exposure to ontology or taxonomy design, and familiarity with taxonomy/ontology management tools (Progress Semaphore, PoolParty, Synaptica, Mondeca, etc.)
  • Experience designing and planning data science projects to meet business requirements
  • Experience implementing agentic AI workflows using frameworks such as LangChain, LlamaIndex, LangGraph, BAML, or equivalent
Salary Information:
EK considers a broad range of factors in considering employee salary including a candidate's skills, experience, education, certifications, past successes, and qualifications. A range for a starting pay for this role is $150,000 to $210,000 with most candidates likely to fall in the lower half. This range does not guarantee a specific salary and may be adjusted based on the needs of the company and the candidate's qualifications.
Data Privacy Notice:
Enterprise Knowledge (EK) is committed to protecting your personal information. When you submit your application, we collect and process your personal data solely for recruitment and hiring purposes. We will not use your information for any other purpose without your explicit consent.
We may share your information with third parties only as necessary to evaluate your application or comply with legal requirements. If we need to use your data for a purpose beyond the original intent or disclose it to additional third parties, we will provide you with prior notice.
You have the right to access the personal information we hold about you and to request corrections, amendments, or deletion of any inaccurate data or data processed in violation of applicable privacy principles. Requests for such changes will be reviewed and accommodated unless the burden or expense of providing access would be disproportionate to the risks to your privacy, or where the rights of other individuals may be affected.
By submitting your application, you acknowledge that you have read and understood this notice. If you have any questions about how we handle your personal data or need to update your information, please contact us at careers@enterprise-knowledge.com

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