We are seeking a Knowledge Graph Engineer to build, optimize, and scale our graph data infrastructure and ingestion pipelines.
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Design, implement, and maintain production knowledge graph architectures using Neo4j.
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Build automated ETL/ELT ingestion pipelines to map relational, semi-structured, and unstructured data into scalable graph schemas.
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Write high-performance Cypher queries and optimize graph indexing, traversal speeds, and memory usage.
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Integrate knowledge graphs with downstream AI/ML workflows and agentic systems (GraphRAG, vector + graph hybrid search).
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Implement data quality checks, entity resolution, and graph lineage monitoring.
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Work Schedule: During the onboarding phase, working hours may be adjusted to overlap with US hours until 7:00 PM at the latest.
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3+ years of hands-on experience designing and operating graph databases, with a strong preference for Neo4j (Aura / Enterprise).
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Expert-level proficiency in Cypher and a solid understanding of graph data modeling (Labeled Property Graphs vs. RDF).
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Strong Python and SQL skills for data transformation, entity linking, and pipeline automation.
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Experience integrating graph databases with modern cloud data platforms (e.g., Databricks, AWS, Azure) or LLM frameworks (LangChain, LlamaIndex).
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Familiarity with semantic modeling concepts and ontology-driven schemas is a strong plus.
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