Graph Database Engineer
- Lead the architecture, design, and implementation of graph-based data solutions.
- Model complex relationships using Labeled Property Graphs (LPG) or RDF/OWL depending on use case.
- Develop and optimize queries using Cypher, Gremlin, SPARQL, or similar graph query languages.
- Collaborate with engineering teams to integrate graph databases with APIs, microservices, or existing data platforms.
- Work closely with stakeholders to define graph use cases (e.g., recommendation engines, fraud detection, knowledge graphs).
- Implement data ingestion pipelines to load, transform, and maintain graph datasets.
- Ensure scalability, performance, and security best practices in graph solutions.
- Mentor junior developers and promote best practices in graph modeling and query design.
- Contribute to proof-of-concepts and evaluate new tools and frameworks in the graph space.
- Document architecture, design decisions, and graph schemas for reusability and governance.
- 10+ years of experience in software development or data engineering roles.
- 3+ years of hands-on experience with graph database technologies (Neo4j, Amazon Neptune, TigerGraph, Stardog, etc.).
- Proficient in one or more graph query languages: Cypher, Gremlin, SPARQL.
- Strong knowledge of data modeling, schema design, and semantic technologies (RDF/OWL a plus).
- Experience with Python, Java, or Scala for integration and data pipeline development.
- Familiarity with data integration tools, ETL pipelines, and APIs for graph ingestion.
- Strong understanding of cloud services (AWS, GCP, or Azure), especially managed graph solutions.
- Experience working in Agile development teams and version-controlled environments (Git, CI/CD).
- Excellent problem-solving, communication, and leadership skills.
- Experience with knowledge graphs, entity resolution, or ontology design.
- Familiarity with machine learning or graph-based AI use cases.
- Prior experience with graph visualization tools (Bloom, Gephi, Linkurious).
- Certifications in Neo4j, AWS Neptune, or relevant cloud/graph platforms.
- Graph Databases: Neo4j, Amazon Neptune, TigerGraph, JanusGraph
- Languages: Cypher, Gremlin, SPARQL, Python, Java, Scala
- Cloud Platforms: AWS (Lambda, S3, Glue), GCP, Azure
- DevOps: Git, Jenkins, Docker, Kubernetes
- Visualization: Neo4j Bloom, Gephi, GraphXR
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