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# Data Science / Knowledge Graph Engineer

- **Company:** VeeRteq Solutions Inc
- **Location:** Chicago, IL, United States
- **Salary:** $92,300.0 - $166,850.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Data Analysis, Computing Platforms, Data Validation, Information Engineering, Data Transformation, Data Systems, Database Queries, Graph Database, Neo4j, Standard Sql, SPARQL, Enterprise Data Management, Data Management, Databricks
- **Published:** August 30, 2026
- **Apply:** https://www.careerjet.com/jobad/us654eea5f4a1d00386aaed45536f6577c

## About the Role

* Hands-on experience with Stardog, Neo4j, GraphDB, or similar graph database/platform technologies.
 * Strong knowledge of semantic modeling.
 * Strong understanding of knowledge graphs.
 * Experience with RDF.
 * Experience with SPARQL.
 * Experience with semantic models and ontologies.
 * Experience with data transformation, mapping, and graph hydration.
 * Strong SQL skills.
 * Strong data analysis skills.
 * Experience validating data quality and troubleshooting graph-related issues.

Preferred Experience

 * Experience with Azure Databricks or similar data platforms.
 * Experience working with data engineering teams and enterprise data platforms.
 * Experience collaborating with AI engineers and architecture teams.

## Description

We are seeking a skilled Data Science / Knowledge Graph Engineer with hands-on experience in semantic modeling, knowledge graphs, graph databases, and data transformation. The ideal candidate will have experience working with platforms such as Stardog, Neo4j, GraphDB, or similar technologies, along with strong SQL and data analysis skills.
The role will focus on understanding domain data and business relationships, designing semantic models and ontologies, building and maintaining knowledge graphs, and developing graph-based data solutions. The resource will collaborate closely with data engineers, architects, domain teams, and AI engineers. Key Responsibilities

 * Understand domain data and business relationships.
 * Design semantic models and ontologies.
 * Build and maintain knowledge graphs.
 * Create source-to-graph mappings and hydrate graphs with data.
 * Develop RDF, OWL, SHACL, and SPARQL queries.
 * Validate data quality and troubleshoot graph-related issues.
 * Perform data transformation and mapping activities required for graph solutions.
 * Work with data engineers, architects, domain teams, and AI engineers to support knowledge graph initiatives.
 * Analyze data and ensure the quality and consistency of graph-related data.
 * Support the development and maintenance of semantic data models and knowledge graph solutions.


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