Neo4J Graph Data Engineer

We are seeking a skilled Data Engineer to lead the planning, execution, and validation of enterprise data migration strategies. You will be responsible for transitioning critical workloads from legacy environments to modern, scalable cloud-based architectures, with a specific focus on graph data structures and financial modeling systems.

Our client is a leading global computer software company known for delivering innovative data-driven solutions. They foster a collaborative, high-performance culture that empowers engineers to solve complex technical challenges at scale.

Responsibilities

• Lead the migration of complex graph database workloads and optimize Cypher queries for cloud environments.
• Refactor, deploy, and maintain robust Java APIs to ensure seamless connectivity within the AWS ecosystem.
• Architect and build high-performance, parallel data streams using AWS Glue, Amazon S3, Lambda, and Athena.
• Develop automated validation scripts to ensure data integrity, schema accuracy, and zero data loss during migration.
• Fine-tune data extraction processes to eliminate on-premise bottlenecks and manage API throttling.
• Utilize Python and PySpark to build and maintain efficient data processing pipelines.

Requirements

• 7-12 years of professional data engineering experience.
• Proven expertise in Neo4J and writing production-grade Cypher queries.
• Strong background in Java development for enterprise APIs and data connectors.
• Hands-on experience integrating SAS or SASFM environments into data pipelines.
• Deep proficiency with the AWS data stack, including AWS Glue, S3, and Athena.
• At least 2 years of dedicated experience migrating legacy workloads to AWS.
• AWS Certified Data Engineer or AWS Certified Solutions Architect certification is highly preferred.