Neo4J Developer

Amaze Systems; Frisco (TX); On-site; USD 120,000 - 180,000; Full time

Job summary

Amaze Systems in Frisco, TX (onsite) seeks a Neo4J Developer to design graph data models, optimize Cypher queries, and build scalable microservices with Java Spring Boot.

You will collaborate with data engineers and product teams to translate business requirements into robust graph and API designs, focusing on high-volume data processing and secure CI/CD practices.

Qualifications

• 5–7 years of software development experience.
• Hands-on Neo4j and Cypher in production environments.
• Strong Java and Spring Boot for building microservices.
• Graph data modeling for complex, interconnected datasets.
• Experience with Git/GitLab and CI/CD pipelines.

Responsibilities

• Design and implement graph data models in Neo4j to support complex relationship-driven use cases.
• Write efficient Cypher queries and tune Neo4j performance for large datasets.
• Develop scalable backend services and APIs using Java and Spring Boot.
• Collaborate with data engineers, architects, and product teams to translate requirements into graph/API designs.
• Participate in code reviews and mentor junior developers on graph DB and Spring Boot practices.

Skills

Neo4J & Cypher

Java Spring Boot

Graph Data Modeling

Git/GitLab & CI/CD

Tools

Snowflake

Kafka

Spark

Docker

Kubernetes

Job description

Job Position: Neo4J Developer (Telecom Domain)

Job Location: Frisco or Kansas (Onsite)

Job Description

Experience :

5+ years of software development experience. Must have strong experience with Neo4J and Java Spring Boot

Mandatory Skills :

Neo4J and Cypher, Java Spring Boot , Graph Data Modeling , Git/GitLab & CI/CD

Duration

12 months

Job Description

• Strong expertise in Neo4j with expertise in Cypher, graph data modeling, schema design, indexing, and query performance tuning at scale. Experience with APOC procedures, graph algorithms (shortest path, centrality, connectivity analysis), and Neo4j clustering/HA setups is a strong plus.
• Deep expertise in Java Spring Boot and related Spring ecosystem in building production-grade microservices and REST APIs for large-volume data processing.
• Designing, building, and maintaining RESTful/GraphQL APIs; API versioning, documentation (OpenAPI/Swagger), and security best practices (OAuth2/JWT).
• Previous experience in Snowflake with background in Querying and optimizing SQL against Snowflake for network KPI reporting, historical trend analysis, and integrating graph-derived insights with enterprise data warehouse layers.
• Experience with Kafka, Spark, or related technology stack for ingesting high-volume, high-frequency data feeds into the graph and downstream systems.

Key Responsibilities

• Design and implement graph data models in Neo4j to support complex relationship-driven use cases
• Write efficient, optimized Cypher queries and tune Neo4j performance for large datasets.
• Develop scalable, secure, and maintainable backend services and APIs using Java and Spring Boot.
• Collaborate with data engineers, architects, and product teams to translate business requirements into technical graph and API designs.
• Participate in code reviews, design discussions, and mentor junior developers on graph database and Spring Boot best practices.
• Troubleshoot and resolve performance bottlenecks across the application and data layer.Ensure adherence to coding standards, security practices, and CI/CD processes

Required Qualifications

• 5–7 years of overall software development experience.
• Proven, hands-on experience with Neo4j and Cypher in production, ideally modeling hierarchical or network/topology data.
• Strong proficiency in Java and Spring Boot for building microservices/APIs.
• Solid understanding of graph data modeling for complex, interconnected datasets.
• Experience with Git/GitLab and CI/CD pipelines.

Preferred Qualifications

• Experience with Snowflake or other cloud data warehouses for enterprise reporting.
• Familiarity with big data/streaming platforms (Kafka, Spark) for high-volume telecom data ingestion.
• Prior exposure to telecom domain concepts: RAN architecture, cell site inventory, network configuration management (CM), OSS/BSS systems, or multi-vendor network equipment (Ericsson, Nokia, Huawei, Samsung, etc.).
• Knowledge of containerization/orchestration (Docker, Kubernetes) and cloud platforms (AWS/Azure/Google Cloud Platform).
• Understanding of network topology visualization and its use in fault management or capacity planning.