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The Role
Design, build, and optimize scalable Neo4j graph database infrastructures supporting knowledge graphs and AI-driven applications. Develop and tune Cypher queries, model complex datasets, manage indexing and performance, and administer backups, recovery, clustering, and scaling. Collaborate with data science and AI teams on graph-based applications, ensure data integrity and security, automate database operations, troubleshoot bottlenecks, and document schemas and procedures.
Summary Generated by Built In
We are seeking a Graph Database Engineer with deep expertise in Neo4j to design, build, and optimize scalable graph data solutions. This role focuses on developing high-performance graph infrastructures that power knowledge graphs and AI-driven applications. The ideal candidate will bring strong hands-on experience with Cypher query optimization, graph data modeling, and database administration. You will work closely with data, engineering, and AI teams to enable efficient data relationships and insights at scale.
Key Responsibilities
- Design and implement scalable graph database architectures using Neo4j.
- Develop, optimize, and maintain complex Cypher queries for high-performance data retrieval.
- Model complex datasets into efficient graph structures aligned with business use cases.
- Monitor and tune database performance, including indexing strategies and query execution plans.
- Manage database operations such as backups, recovery, clustering, and scaling.
- Collaborate with data scientists and AI teams to support knowledge graph and RAG-based applications.
- Ensure data integrity, consistency, and security across graph systems.
- Troubleshoot performance bottlenecks and implement improvements in query and schema design.
- Automate routine database maintenance and monitoring tasks.
- Document graph schemas, data flows, and operational procedures for internal stakeholders.
Requirements
Required Qualifications
- Strong hands-on experience with Neo4j in production environments.
- Proficiency in writing and optimizing Cypher queries for large-scale datasets.
- Solid understanding of graph data structures, relationships, and traversal techniques.
- Experience with indexing, query planning, and performance tuning in graph databases.
- Knowledge of database administration including backup, recovery, and clustering.
- Familiarity with integrating graph databases into application ecosystems via APIs or services.
- Experience working with large, complex datasets in distributed environments.
- Understanding of data modeling principles for knowledge graphs or connected data systems.
Preferred Qualifications
- Experience with graph-based AI/ML use cases such as recommendation systems or fraud detection.
- Exposure to Neo4j Aura or other managed graph database services.
- Familiarity with ETL pipelines and data ingestion into graph databases.
- Experience working with cloud platforms (AWS, GCP, or Azure).
- Knowledge of other database systems (SQL/NoSQL) and data integration patterns.
Experience Requirements
- 3–6 years of experience in database engineering or backend development.
- At least 2+ years of hands-on experience with Neo4j or other graph databases.
- Proven experience working on data-intensive applications or graph-based systems.
Skills Required
- Strong hands-on experience with Neo4j in production environments
- Proficiency writing and optimizing Cypher queries for large-scale datasets
- Understanding of graph data structures, relationships, and traversal techniques
- Experience with indexing, query planning, and performance tuning in graph databases
- Knowledge of database administration, including backup, recovery, and clustering
- Experience integrating graph databases into application ecosystems via APIs or services
- Experience working with large, complex datasets in distributed environments
- Understanding of data modeling principles for knowledge graphs or connected data systems
- Experience with graph-based AI/ML use cases such as recommendation systems or fraud detection
- Exposure to Neo4j Aura or other managed graph database services
- Familiarity with ETL pipelines and data ingestion into graph databases
- Experience working with AWS, GCP, or Azure
- Knowledge of other SQL/NoSQL database systems and data integration patterns
- 3-6 years of experience in database engineering or backend development
- At least 2 years of hands-on experience with Neo4j or other graph databases
- Proven experience working on data-intensive applications or graph-based systems
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The Company
What We Do
Agivant Technologies is a new-age, AI-first digital and cloud engineering services company. It helps enterprises use cutting-edge technology, AI, automation, and platform engineering to create new business models, accelerate growth, and deliver measurable impact. The company also emphasizes a dual mission: driving client business success while expanding access to opportunities for technology talent in underserved, mid-tier locations across global markets.
