Senior Knowledge Graph Data Engineer

SELECT* is a professional team of recruiting specialists who are searching for talents in Ukraine, Europe, and the USA. Currently, we are looking for a Senior Knowledge Graph Data Engineer for XTEL.

Join XTEL as a Senior Knowledge Graph Data Engineer to design and implement the next-generation data infrastructure that powers AI-driven systems. Lead the architecture, integration, and scaling of our enterprise knowledge graph to support intelligent search, reasoning, and LLM-powered agents. Collaborate with ontology engineers, AI developers, and data teams to align business logic with semantic architecture. This is a strategic technical role with end-to-end ownership of the knowledge graph stack.

Key Responsibilities

• Design and lead the architecture of our knowledge graph platform, ensuring scalability, performance, and semantic interoperability.
• Integrate data from diverse sources (structured, unstructured, relational, etc.) into graph-based models aligned with business ontologies.
• Collaborate with ontology engineers to align conceptual models with data infrastructure and schema implementations.
• Define best practices for graph data ingestion, modeling, indexing, versioning, and querying (e.g., SPARQL, GraphQL, Cypher).
• Select and configure graph databases and associated technologies (e.g., RDF triple stores, property graphs, reasoning engines).
• Work closely with AI teams to enable LLM agents and semantic search over the knowledge graph.
• Mentor team members and guide technical decision-making around graph modeling, tooling, and standards.
• Stay current with trends in semantic technologies, graph databases, and data architecture.

Qualifications

• A Bachelor’s or Master’s degree in Computer Science, Data Engineering, or a related field.
• At least 7 years of experience in data architecture, with 3+ years focused on knowledge graphs or graph data platforms.
• Deep knowledge of RDF, OWL, or property graph technologies (e.g., Neo4j, GraphDB, Stardog, Blazegraph, Amazon Neptune).
• Hands-on experience designing and maintaining scalable knowledge graph systems across large or complex data domains.
• Proficiency in data modeling, transformation, integration (ETL/ELT), and graph query languages (SPARQL, Cypher, etc.).
• Strong understanding of the interplay between ontologies, semantics, and graph data infrastructure.
• Advanced proficiency in English, with excellent written and verbal communication skills.

Nice to have

• Experience deploying reasoning engines or hybrid symbolic-ML systems.
• Familiarity with integrating LLMs or AI agents on top of knowledge graphs.