Neo4j Data Engineer.
This mandate is run by SYMPHONI HR, a Mumbai-based executive search firm, est. 2003. Applications are email-verified and reach the search team running the role — confidentially, always.
About the organisation.
Our client is a prominent global leader in the computer software industry, known for delivering innovative data-driven solutions. They foster a collaborative and high-performance culture that empowers engineers to solve complex technical challenges at scale. With a commitment to excellence, they provide a dynamic environment for professionals to grow their expertise in cutting-edge technologies.
About the role.
We are looking for a highly skilled Data Engineer to join our team in a hybrid capacity. You will be responsible for architecting and maintaining robust data engineering solutions, with a specific focus on leveraging Neo4j and the Hadoop ecosystem to drive enterprise-scale graph database initiatives.
What you will do.
- Design, develop, and maintain scalable data engineering solutions within the Hadoop ecosystem.
- Develop and optimize Neo4j graph database solutions, focusing on high-performance data ingestion and retrieval.
- Author and refine complex Cypher queries to ensure efficient data analysis and processing.
- Build and manage end-to-end data pipelines, utilizing PySpark Parallel Loader for seamless Neo4j integration.
- Monitor, troubleshoot, and optimize performance for both data processing jobs and graph database workloads.
- Collaborate with architects, data scientists, and stakeholders to translate business requirements into technical solutions.
- Uphold rigorous standards for data quality, governance, security, and technical documentation.
- Participate in peer code reviews and contribute to the establishment of engineering best practices.
What you bring.
- 8–11 years of professional experience in Data Engineering.
- 3–5 years of hands-on experience with Neo4j Graph Database, including advanced Cypher query optimization.
- Strong practical experience with PySpark and Hadoop clusters.
- Proven ability to load and manage data in Neo4j using PySpark Parallel Loader.
- Deep understanding of data modeling, ETL/ELT workflows, and distributed computing principles.
- Demonstrated success in troubleshooting performance bottlenecks within complex data pipelines.
- Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field.
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