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Semantic Data Analyst Jobs (NOW HIRING)

EASE Logistics

Senior Data Analyst

Dublin, OH · On-site

$81K - $102K/yr

Develop and manage semantic data models in Power BI using DAX, including measures, calculated columns, and row-level security (RLS). * Analyze and tune underperforming reports and queries to improve ...

Persistent Systems

Data Analyst

Manhattan, NY · On-site

The Data Analyst will transform complex operational, financial, customer, product, and program data ... This role will build trusted datasets, semantic models, dashboards, and analyses that help leaders ...

Persistent Systems

Data Analyst

Manhattan, NY · On-site

The Data Analyst will transform complex operational, financial, customer, product, and program data ... This role will build trusted datasets, semantic models, dashboards, and analyses that help leaders ...

Persistent Systems

Data Analyst

Manhattan, NY · On-site

The Data Analyst will transform complex operational, financial, customer, product, and program data ... This role will build trusted datasets, semantic models, dashboards, and analyses that help leaders ...

Persistent Systems

Data Analyst

Manhattan, NY · On-site

The Data Analyst will transform complex operational, financial, customer, product, and program data ... This role will build trusted datasets, semantic models, dashboards, and analyses that help leaders ...

CSAA

Job Title Sr. Manager, AI Lead - Semantic Layer - Remote Requisition Number R7755 Sr. Manager, AI ... Support both structured and unstructured data integration, enabling downstream AI and analytics ...

CSAA

Job Title Sr. Manager, AI Lead - Semantic Layer - Remote Requisition Number R7755 Sr. Manager, AI ... Support both structured and unstructured data integration, enabling downstream AI and analytics ...

Robert Half

Data Analyst

New Holland, PA · On-site

$100K - $110K/yr

Manage datasets, semantic models, report distributions, and reporting governance processes ... Data Analysis, Data Warehousing, SQL, Python, Insurance Companies, Property Casualty Insurance ...

CSAA

Job Title Sr. Manager, AI Lead - Semantic Layer - Remote Requisition Number R7755 Sr. Manager, AI ... Support both structured and unstructured data integration, enabling downstream AI and analytics ...

CSAA

Job Title Sr. Manager, AI Lead - Semantic Layer - Remote Requisition Number R7755 Sr. Manager, AI ... Support both structured and unstructured data integration, enabling downstream AI and analytics ...

CSAA

Job Title Sr. Manager, AI Lead - Semantic Layer - Remote Requisition Number R7755 Sr. Manager, AI ... Support both structured and unstructured data integration, enabling downstream AI and analytics ...

CSAA

Job Title Sr. Manager, AI Lead - Semantic Layer - Remote Requisition Number R7755 Sr. Manager, AI ... Support both structured and unstructured data integration, enabling downstream AI and analytics ...

CSAA

Job Title Sr. Manager, AI Lead - Semantic Layer - Remote Requisition Number R7755 Sr. Manager, AI ... Support both structured and unstructured data integration, enabling downstream AI and analytics ...

CSAA

Job Title Sr. Manager, AI Lead - Semantic Layer - Remote Requisition Number R7755 Sr. Manager, AI ... Support both structured and unstructured data integration, enabling downstream AI and analytics ...

CSAA

Job Title Sr. Manager, AI Lead - Semantic Layer - Remote Requisition Number R7755 Sr. Manager, AI ... Support both structured and unstructured data integration, enabling downstream AI and analytics ...

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Semantic Data Analyst information

See salary details

$34K

$82.6K

$136K

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.

Senior Data Analyst

Dublin, OH • On-site

EASE Logistics
Transportation and Warehousing • 51 - 200 employees
Learn more about EASE Logisticsexternal

$81K - $102K/yr

Full-time

This job post has expired 2 days ago. Applications are no longer accepted.

Job description

ESSENTIAL DUTIES

Reporting & Dashboard Development

  • Design, build, and maintain Power BI dashboards and reports for operations, finance, sales, and executive stakeholders.
  • Develop and manage semantic data models in Power BI using DAX, including measures, calculated columns, and row-level security (RLS).
  • Analyze and tune underperforming reports and queries to improve load times and reliability.
  • Establish and document self-service BI standards and a shared metrics catalog.

Data & SQL

  • Write complex T-SQL queries, CTEs, window functions, multi-table joins against Azure SQL and Microsoft Fabric.
  • Collaborate with data engineers to define data requirements, validate pipeline outputs, and ensure data quality upstream of reporting.
  • Identify data anomalies and inconsistencies; work upstream to resolve at the source rather than patching in reports.

Stakeholder Collaboration

  • Partner with department leaders across operations, finance, and customer experience to translate business questions into measurable data products.
  • Lead requirements-gathering sessions and translate ambiguous requests into defined scopes with clear deliverables and timelines.
  • Communicate findings clearly to non-technical audiences — written, visual, and verbal.
  • Contribute to special projects, operational improvement initiatives, and data-driven strategy efforts.

Team & Process

  • Recommend and implement process improvements within the analytics function.
  • Uphold data governance, security, and confidentiality standards across all reporting environments.
  • Participate in sprint planning and contribute to team workflows using Azure DevOps or equivalent tooling.

Qualifications

Education

  • Bachelor’s degree preferred in a quantitative field (Computer Science, Statistics, Mathematics, Information Systems).
  • Equivalent professional experience (4+ years) accepted in lieu of degree.
  • Transportation or logistics industry background is a strong plus.

Experience

  • Required- 4+ years of hands-on experience in a BI, data analytics, or reporting analyst role.
  • Required- Expert-level Power BI — semantic modeling, DAX (measures vs. calculated columns), RLS, gateways, and deployment pipelines.
  • Required- Strong T-SQL — complex queries, CTEs, window functions, query optimization; experience with Azure SQL Database.
  • Required - Proven ability to work with messy, multi-source operational data — not just clean, pre-modeled datasets.
  • Preferred - Experience with Microsoft Fabric, Azure Synapse Analytics, OneLake architecture and Fabric lakehouses or warehouses or comparable cloud data platform.
  • Preferred - Direct experience with McLeod TMS data preferred (orders, loads, lanes, drivers, invoicing).
  • Preferred - Experience in logistics, transportation, supply chain, or a similarly operations-heavy industry.

Knowledge, Skills, & Abilities

  • Ability to communicate complex data findings to non-technical stakeholders clearly and confidently.
  • Ability to adapt and work in a fast-paced, operations-heavy environment.
  • Strong problem-solving skills; comfortable working with ambiguous or incomplete requirements.
  • Experience with ADF or analytics engineering practices for building and testing data models preferred.
  • Python or R for exploratory analysis and data prep preferred.
  • Azure DevOps or Git-based version control for BI asset deployment preferred.
  • Power BI Premium / Fabric capacity management, workspace governance, and admin experience preferred.

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