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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in designing and maintaining knowledge graph architectures, particularly with Neo4j, while integrating with AI/ML workflows and ensuring data quality through effective ETL/ELT processes.
Highest-signal resume keywords
Neo4j Database DesignCypher Query OptimizationGraph Data ModelingPython Data TransformationCloud Data Platform Integration
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Graph Database DesignCypher ProficiencyData TransformationEntity LinkingPipeline AutomationGraph IndexingGraph Traversal OptimizationData Quality ChecksEntity ResolutionGraph Lineage Monitoring
Tools & Technologies
Neo4j AuraNeo4j EnterpriseDatabricksAWSAzureLangChainLlamaIndex
Industry Keywords
Knowledge GraphsETLELTSemantic ModelingOntology-Driven Schemas
Tech Stack
Tools & technologiesAWSAzureCloudETLNeo4jPythonSQL
About the role
Key responsibilities & impact- 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, including GraphRAG and vector + graph hybrid search
- Implement data quality checks, entity resolution, and graph lineage monitoring
Requirements
What you’ll need- 3+ years of hands-on experience designing and operating graph databases, with a strong preference for Neo4j (Aura / Enterprise)
- Expert-level proficiency in Cypher
- 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