Neo4J Data engineer

Role & responsibilities

• Design, develop, and maintain data engineering solutions using PySpark and Hadoop ecosystems. • Develop and optimize Neo4j graph database solutions for enterprise-scale applications. • Write, enhance, and optimize Cypher queries for efficient data ingestion, retrieval, and analysis. • Build and maintain data pipelines for loading and processing large volumes of data. • Implement data loading solutions into Neo4j using PySpark Parallel Loader and related integration frameworks. • Monitor, troubleshoot, and optimize performance of data processing jobs and graph database workloads. • Collaborate with architects, data scientists, and business stakeholders to understand requirements and deliver technical solutions. • Ensure data quality, integrity, governance, and security standards are maintained. • Participate in code reviews, technical design discussions, and best practice implementation. • Create technical documentation and present solutions to technical and non-technical stakeholders.

Required skills :

6-10 years of overall experience in Data Engineering.

• Hands-on experience with PySpark and Hadoop clusters.

• 3-5 years of hands-on experience with Neo4j Graph Database.

• Strong expertise in writing and optimizing Cypher queries for data read/write operations.

• Experience loading and managing data in Neo4j using PySpark Parallel Loader.

• Strong understanding of data modeling, ETL/ELT processes, and distributed computing concepts.

• Experience troubleshooting performance issues and optimizing data pipelines.