About the Role :

We are looking for a skilled Neo4j Developer with strong hands-on experience in Neo4j, Cypher, Graph Data Modeling, and Neo4j Graph Data Science (GDS). The role involves designing and developing graph-based solutions, building data ingestion pipelines, applying graph analytics, and productionizing Neo4j solutions.

Key Responsibilities :

- Design and implement scalable property graph data models for use cases such as Customer 360, fraud detection, journey analytics, and supply chain.

- Develop complex Cypher queries, procedures, and APOC utilities.

- Build data ingestion pipelines using Kafka, Spark, REST APIs, Python/Java drivers, and other integration methods.

- Manage batch and streaming data loads, indexes, constraints, and data quality.

- Use Neo4j GDS algorithms such as PageRank, Louvain, WCC, Shortest Path, and node embeddings.

- Develop feature-engineering workflows and integrate graph analytics with Python/Scikit-learn or ML frameworks.

- Optimize graph queries and improve database performance.

- Support Neo4j deployment, monitoring, security, backups, and clustering.

- Follow engineering practices including Git, CI/CD, unit testing, and integration testing.

Mandatory Skills :

- 2+ years of hands-on Neo4j experience.

- Strong Cypher and Graph Data Modeling skills.

- Hands-on experience with Neo4j GDS.

- Strong Python or Java programming skills.

- Experience with APOC, indexes, constraints, and query optimization.

- Knowledge of graph modeling concepts including supernodes, bridge nodes, canonical entities, and time-versioned relationships.

- Experience with ETL/data integration technologies such as Kafka, Spark, Airflow, or dbt.