Neo4j Graph Database Engineer

Net2Source (N2S); Charlotte (NC); On-site; USD 90,000 - 120,000; Full time

Job summary

Net2Source (N2S) is searching for a Graph Database Engineer in Charlotte, NC, to design and deliver graph-based fraud detection solutions using Neo4j. The role includes modeling complex relationships to uncover fraud patterns, optimizing Cypher queries, and maintaining data pipelines. Candidates should have 4 to 8 years of IT experience with strong proficiency in graph databases and analytical skills. This contract position emphasizes collaboration with fraud analysts and data scientists.

Qualifications

• 4 to 8 years of overall IT experience.
• Strong hands-on experience with Neo4j Graph Database.
• Solid expertise in Cypher query language.
• Good understanding of graph data modeling and graph concepts.
• Experience with fraud, AML, risk, or financial analytics use cases.

Responsibilities

• Design and implement Neo4j graph data models for fraud and risk analytics.
• Develop, optimize, and maintain Cypher queries for deep relationship traversal.
• Support fraud use cases such as entity resolution and fraud rings.
• Build and maintain data ingestion pipelines from various sources.
• Perform query tuning, indexing, and schema optimization.
• Integrate Neo4j with applications and services.
• Collaborate with other teams to translate requirements into graph solutions.
• Assist in production support, troubleshooting, and monitoring graph platforms.

Skills

Neo4j Graph Database

Cypher query language

Python

Java

Analytical skills

Job description

Position Type: Contract

JOB DESCRIPTION

We are seeking a Graph Database Engineer with strong hands on experience in Neo4j to design and deliver graph based fraud detection solutions.

The role focuses on modeling complex relationships across transactions, customers, accounts, devices, and merchants to uncover hidden fraud patterns and networks.

You will work closely with fraud analysts, data engineers, and data scientists to enable both real time and investigative fraud use cases.

Key Responsibilities

• Design and implement Neo4j graph data models for fraud and risk analytics
• Develop, optimize, and maintain Cypher queries for deep relationship traversal and pattern detection
• Support fraud use cases such as entity resolution, fraud rings, collusion analysis, and network exploration
• Build and maintain data ingestion pipelines from RDBMS, data lakes, files, and streaming sources
• Perform query tuning, indexing, and schema optimization for performance and scalability
• Integrate Neo4j with applications and services using drivers, APIs, or microservices
• Collaborate with fraud, analytics, and engineering teams to translate requirements into graph solutions
• Assist in production support, troubleshooting, and monitoring of graph platforms
• Contribute to documentation, best practices, and platform improvements

Required Skills & Qualifications

• 4 to 8 years of overall IT experience
• Strong hands on experience with Neo4j Graph Database
• Solid expertise in Cypher query language
• Good understanding of graph data modeling and graph concepts
• Experience working on fraud, AML, risk, or financial analytics use cases
• Proficiency in Python and/or Java
• Experience with ETL/ELT pipelines and data integration
• Familiarity with performance tuning, indexing, and constraints in Neo4j
• Strong analytical, problem solving, and communication skills