- 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 :
- 7 - 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.
- Solid 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.
Education : Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field.
📌 Data Engineer - Neo4j (India)
🏢 wowJobs
📍 India
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