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Data Engineer (Neo4j / GraphRAG)

The Workly·Salary not specified

Primary stack

PythonTypeScriptNeo4j

Nice to have's

regulated enterprise domainsvector databasesmulti-agent systemssemantic modelsontologiesknowledge engineering

Job description

About the Position

Your vision. Our solutions.

We are building the core memory and retrieval layer for agentic AI systems operating over large-scale enterprise data. This role focuses on designing and operating high-quality data pipelines that move data from a cloud lakehouse into a Neo4j-backed semantic graph optimized for agent reasoning and GraphRAG retrieval.

This is a hands-on data engineering role, prioritizing pipeline automation, graph construction, performance tuning, and reliability over academic ontology design. Your work enables agents to retrieve accurately, reason reliably, and operate with enterprise-grade context and traceability.

Responsibilities

  • Build and maintain ETL/ELT pipelines from Microsoft Fabric (or similar) into Neo4j
  • Transform structured and unstructured data into clean graph models (nodes, edges, metadata)
  • Implement automated ingestion, delta updates, and streaming/CDC patterns
  • Implement and maintain Neo4j graph structures, indexes, constraints, and performance tuning
  • Develop Cypher queries, APOC procedures, and ingestion utilities
  • Enable GraphRAG structures (entities, chunks, embeddings) for high-quality retrieval
  • Optimize graph-based retrieval for agent workflows (hybrid search, entity linking)
  • Ensure data quality, lineage, auditability, and monitoring
  • Collaborate closely with AI Architects, Agent Developers, and UX/AX teams

Requirements

  • Strong Data Engineering background (pipelines, orchestration, modeling)
  • Hands-on Neo4j experience: Cypher, APOC, graph modeling Bulk ingestion, indexing, performance tuning
    • Cypher, APOC, graph modeling
    • Bulk ingestion, indexing, performance tuning
  • Experience with Microsoft Fabric, Synapse, ADF, or similar cloud data platforms
  • Familiarity with GraphRAG, retrieval systems, or RAG hybrids
  • Comfortable with Python or TypeScript for pipelines and APIs
  • Understanding of LLM behavior and agentic retrieval workflows (preferred)

Nice to Have

  • Experience in regulated enterprise domains (banking, finance, operations)
  • Familiarity with vector databases and embedding pipelines
  • Experience supporting multi-agent or AI-driven systems
  • Exposure to semantic models, ontologies, or knowledge engineering

We Offer

  • Remote work in Europe
  • Opportunity to work with cutting-edge AI technologies

About the Company

The Workly s.r.o.

4D CENTER, Kodaňská 1441/46,

101 00, Praha 10.

Contact: [email protected] + 420 775 371 991

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