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Wallet icon Coin icon Rate 160 000 CZK - 179 960 CZK / month info
Timer icon Form of cooperation Full-time / 95% Remote
Briefcase icon Sector Information Technology
Location icon Location Praha

info The reward is calculated upon delivery of 20 MD per month (1MD=8h)

Project duration 12 months with the possibility of extension
Period of cooperation 19.01.2026 - 18.01.2027
Start date 19.01.2026 asap
Technology
  • Python
Languages
  • English flag English - active, B2/C1/C2

Project description

  • development and maintenance of ETL/ELT data pipelines from Microsoft Fabric Lakehouse to Neo4j
  • transformation of structured and unstructured data into nodes, edges, and metadata
  • implementation of automated ingestion processes including delta and CDC workflows
  • optimization of performance and scalability of data flows for agent retrieval
  • construction of graph structures according to the design of AI architects (indexes, constraints, relationships)
  • creation of Cypher scripts and utilization of APOC procedures for robust data loading
  • implementation of GraphRAG structures (e.g., embeddings, entity, chunky) to improve search
  • integration of graph endpoints into agent pipelines (retrieval functions, Cypher API)
  • ensuring data quality including logging, monitoring, auditing, and metadata management
  • close collaboration with architects, agent developers, and the UX team on the design of retrieval interfaces

Project requirements

  • minimum 5 years of experience in data engineering, ETL/ELT, and data modeling
  • demonstrable knowledge of Neo4j including Cypher, APOC, indexing, and performance optimization
  • extensive experience with Microsoft Fabric, Azure Synapse, ADF, or similar cloud stack
  • excellent ability to design and operate scalable data pipelines
  • demonstrable experience with pipeline automation and orchestration (e.g., Airflow, dbt, Data Factory)
  • good knowledge of Python or TypeScript for developing data flows and API interfaces
  • excellent analytical skills and orientation in complex enterprise data
  • experience with GraphRAG or retrieval augmented generation is an advantage
  • knowledge of agent systems and LLM workflows is an advantage
  • excellent communication skills in English 
  • ability to collaborate across teams
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