Lead Graph Data Engineer - Neo4j
Acunor Inc
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.
Key Responsibilities- 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.
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