Knowledge Graph Engineer

We are seeking a Knowledge Graph Engineer to build, optimize, and scale our graph data infrastructure and ingestion pipelines.

Daily tasks

• Design, implement, and maintain production knowledge graph architectures using Neo4j.
• Build automated ETL/ELT ingestion pipelines to map relational, semi-structured, and unstructured data into scalable graph schemas.
• Write high-performance Cypher queries and optimize graph indexing, traversal speeds, and memory usage.
• Integrate knowledge graphs with downstream AI/ML workflows and agentic systems (GraphRAG, vector + graph hybrid search).
• Implement data quality checks, entity resolution, and graph lineage monitoring.
• Work Schedule: During the onboarding phase, working hours may be adjusted to overlap with US hours until 7:00 PM at the latest.

Requirements

• 3+ years of hands-on experience designing and operating graph databases, with a strong preference for Neo4j (Aura / Enterprise).
• Expert-level proficiency in Cypher and a solid understanding of graph data modeling (Labeled Property Graphs vs. RDF).
• Strong Python and SQL skills for data transformation, entity linking, and pipeline automation.
• Experience integrating graph databases with modern cloud data platforms (e.g., Databricks, AWS, Azure) or LLM frameworks (LangChain, LlamaIndex).
• Familiarity with semantic modeling concepts and ontology-driven schemas is a strong plus.

Must have: Neo4j, Python, Cypher, Knowledge Graphs, Graph Data Modeling, SQL, ETL, ELT, GraphRAG / Hybrid Search, Entity Resolution / Entity Linking, Cloud Data Platforms & LLM Frameworks