Job Title: Backend Java Developer (with Neo4j Infrastructure Expertise)
Location: San Diego, CA
Pay Rate : On C2C
Job Summary:
We are seeking a skilled Backend Java Developer with hands-on experience in managing Neo4j infrastructure. The ideal candidate will have a strong background in Java development and be capable of deploying, maintaining, and optimizing Neo4j graph databases in production environments. This role bridges backend engineering with graph database infrastructure operations.
Key Responsibilities:
- Develop and maintain scalable backend services using Java, Spring Boot, and related technologies
- Design and integrate graph-based data models using Neo4j
- Write efficient and optimized Cypher queries for application use cases
- Manage the deployment, configuration, monitoring, and scaling of Neo4j instances (on-premises or in the cloud)
- Ensure database reliability, availability, and performance in production and staging environments
- Implement backup, recovery, and security strategies for Neo4j databases
- Collaborate with DevOps teams to integrate Neo4j into CI/CD pipelines and monitoring systems
- Analyze and tune query and indexing performance
- Support developers and analysts with graph data access and model design
Required Qualifications:
- Bachelor’s or Master’s degree in Computer Science, Software Engineering, or a related field
- 3+ years of experience in backend development with Java and Spring Boot
- 1+ years of hands-on experience managing Neo4j infrastructure in production environments
- Proficiency with Cypher query language and graph data modeling
- Experience with system administration tasks related to databases (e.g., backups, monitoring, tuning)
- Familiarity with Docker, Kubernetes, or containerized deployments
- Understanding of Linux environments and shell scripting
- Experience with DevOps tools like Prometheus, Grafana, Ansible, or Terraform
Preferred Qualifications:
- Experience deploying Neo4j in high-availability or clustered environments
- Knowledge of Neo4j Aura, K8s Operator, or Graph Data Science (GDS) library
- Exposure to cloud platforms (AWS, GCP, Azure) – especially Amazon EC2, EKS, or GCP Compute Engine
- Familiarity with message queues (Kafka, RabbitMQ) and microservices architectures
- Prior experience with graph use cases like recommendation engines, fraud detection, or knowledge graphs