Description

You will build and manage highly connected data environments using native graph storage and processing. You own the lifecycle of graph systems, from design to cloud deployment.

Responsibilities

• Build, query, and analyze connected data using Neo4j native graph storage and processing.
• Design, develop, and optimize complex, data-intensive ETL processes.
• Engineer graph systems for performance, scalability, latency, and reliability.
• Manage graph clustering, high availability, and cloud-based graph implementations.
• Integrate graphs with Spark and utilize built-in ETL and integration support.

Required Skills

• Deep experience with Neo4j, including graph scalability and clustering.
• Proficiency in Cypher scripting.
• Hands-on experience with Java, Python, or .Net.
• Experience with AWS, Azure, or GCP.
• Ability to manage graphs in the cloud and on Spark.
• Experience troubleshooting complex data-intensive ETL pipelines.
• Degree in any field of study.

Preferred Skills

• Experience with DevOps and automation.

Key Skills

Education

Any graduate