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Semantic Data Analyst Jobs (NOW HIRING)

... power analytics, data products, decisioning, and AI experiences. This is a highly visible ... Build semantic business objects that bring together enterprise data, business context ...

Ensure semantic consistency across analytics, ML, and operational systems LLM & Applied AI Systems * Design and build retrieval-augmented generation (RAG) systems grounded in semantic data

... power analytics, data products, decisioning, and AI experiences. This is a highly visible ... Build semantic business objects that bring together enterprise data, business context ...

Senior Semantic Data Architect

Houston, TX ยท On-site

$123K - $168K/yr

We are seeking a talented Senior Semantic Data Architect to join our team SUMMARY: This position is ... AI, analytics, and data products. The role partners with subject matter experts, AI Program ...

... power analytics, data products, decisioning, and AI experiences. This is a highly visible ... Build semantic business objects that bring together enterprise data, business context ...

$78K - $106K/yr

... power analytics, data products, decisioning, and AI experiences. This is a highly visible ... Build semantic business objects that bring together enterprise data, business context ...

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Semantic Data Analyst information

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$34K

$82.6K

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How much do semantic data analyst jobs pay per year?

As of Sep 11, 2026, the average yearly pay for semantic data analyst in the United States is $82,640.00, according to ZipRecruiter salary data. Most workers in this role earn between $62,500.00 and $97,000.00 per year, depending on experience, location, and employer.

What is a semantic data analyst?

A Semantic Data Analyst is a professional who specializes in interpreting, organizing, and analyzing data using semantic technologies. They work with ontologies, taxonomies, and metadata to add meaning and context to data, making it more useful for complex analysis and machine learning applications. Semantic Data Analysts help organizations structure their data, improve searchability, and enable smarter data integration by focusing on the relationships and meanings within data sets. Their work often involves using tools and languages such as RDF, OWL, and SPARQL to manage and query semantic data.

What are the key skills and qualifications needed to thrive as a semantic data analyst?

To thrive as a Semantic Data Analyst, you need a strong background in data analysis, knowledge representation, and experience with ontologies, often supported by a degree in computer science or information science. Proficiency with semantic web technologies such as RDF, OWL, SPARQL, and familiarity with data integration tools and graph databases is typically required. Strong analytical thinking, attention to detail, and effective communication skills help you interpret complex data relationships and explain insights to stakeholders. These skills are crucial for extracting meaningful insights from structured data, enabling effective decision-making and knowledge management within organizations.

How does a semantic data analyst typically collaborate with other teams within an organization?

Semantic Data Analysts often work closely with data engineers, software developers, and subject matter experts to ensure that data is accurately structured, labeled, and interpreted according to organizational needs. They play a key role in translating business requirements into semantic models or ontologies, which helps improve data interoperability and accessibility. Regular meetings with cross-functional teams are common, as analysts provide guidance on metadata standards and support the integration of semantic technologies into various projects.

What is the difference between Semantic Data Analyst vs Data Analyst?

AspectSemantic Data AnalystData Analyst
Required CredentialsBachelor's in Data Science, Computer Science, or related field; knowledge of semantic web technologiesBachelor's in Data Analysis, Statistics, or related field; proficiency in Excel, SQL, and data visualization tools
Work EnvironmentData-driven projects, semantic web platforms, knowledge graphsBusiness intelligence, reporting, data cleaning, and visualization
Industry UsageTech, research, organizations utilizing semantic web and linked dataFinance, marketing, healthcare, and general business sectors

The Semantic Data Analyst specializes in semantic web technologies and linked data, focusing on structuring and interpreting data within knowledge graphs. In contrast, the Data Analyst primarily handles data collection, cleaning, and visualization for business insights. Both roles require strong analytical skills, but the Semantic Data Analyst's expertise in semantic technologies distinguishes their focus on web semantics and knowledge representation.

What are popular job titles related to Semantic Data Analyst jobs?

For Semantic Data Analyst jobs, the most frequently searched job titles are:

Infographic showing various Semantic Data Analyst job openings in the United States as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 84% Full Time, 11% Part Time, and 3% Contract. Highlights an 85% Physical, 3% Hybrid, and 12% Remote job distribution, with an average salary of $82,640 per year, or $39.7 per hour.

Semantic Data and AI Engineer

Arlington, VA โ€ข On-site

Enterprise Knowledge, LLC
11 - 50 employees

$131K - $158K/yr

Other

This job post hasย expired today.ย Applications are no longer accepted.


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 cuttingโ€‘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 fastโ€‘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.

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 AIโ€‘ready assets
  • Design, implement, test, and operate endโ€‘toโ€‘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 AIโ€‘based solutions
  • Analyze complex datasets and communicate insights to both technical and nonโ€‘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

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
  • Bachelorโ€™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
  • Handsโ€‘on experience building and optimizing RAG pipelines, including embedding strategies, reranking, and crossโ€‘encoder models
  • Familiarity with retrieval quality and evaluation metrics (precision, recall, MRR, and userโ€‘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 candidateโ€™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 candidateโ€™s qualifications.

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