Lead Graph Data Engineer Neo4j

Experience: 12 15 Years
Location:Remote

Job Summary

We are seeking an experienced Lead Graph Data Engineer with strong expertise in graph databases, data engineering, and cloud-native architectures.

The ideal candidate will have hands-on experience designing and deploying production-grade graph solutions using AWS Neptune or Neo4j, building scalable data pipelines, and integrating knowledge graphs with AI/LLM applications.

This role requires strong technical ownership, expertise in graph modeling and query optimization, and the ability to establish engineering standards while mentoring team members.

• Design and implement graph data models, knowledge graphs, and ontologies for complex business datasets.
• Build, deploy, optimize, and maintain production-grade graph databases using AWS Neptune or Neo4j.
• Develop scalable batch and streaming data pipelines for graph data ingestion and transformation.
• Write, optimize, and troubleshoot graph queries using Cypher, Gremlin, or SPARQL.
• Integrate knowledge graphs with Large Language Models (LLMs) to support GraphRAG and semantic search applications.
• Leverage AWS data services to build reliable, scalable graph data solutions.
• Develop and maintain data engineering components using Python or Java.
• Work with distributed processing and orchestration technologies such as Apache Spark, Kafka, or Airflow.
• Implement infrastructure automation using Infrastructure as Code (IaC) practices.
• Establish graph engineering standards, promote best practices, and mentor engineers.

• Bachelor's degree with 12 15 years of experience in Data Engineering, including at least 3 years of hands-on production graph engineering experience.
• Strong hands-on expertise with AWS Neptune or Neo4j in production environments.
• Experience designing graph models, ontologies, and graph-based data architectures.
• Proficiency in at least one graph query language: Cypher, Gremlin, or SPARQL.
• Strong programming skills in Python or Java.
• Practical experience with AWS cloud infrastructure and data services.
• Experience with at least one of the following: Apache Spark, Apache Kafka, or Apache Airflow.
• Experience implementing Infrastructure as Code (IaC).
• Understanding of AI/LLM integration with graph databases, particularly GraphRAG and semantic search.
• Ability to provide technical guidance, mentor engineers, and establish engineering standards.

• Experience with RDF, OWL, and semantic web technologies.
• Knowledge of graph algorithms and graph analytics.
• Exposure to LangChain or similar LLM orchestration frameworks.
• Experience with vector databases and hybrid graph-vector retrieval architectures.
• AWS or Neo4j certifications.