Neo4J Data engineer

EXL; Pune District, Bengaluru, Delhi; Hybrid; INR 2,600,000 - 4,000,000; Full time

Benefits offered by this job

Health insurance

Job summary

EXL in Pune, India is seeking an experienced Data Engineer to design, develop, and maintain data engineering solutions using PySpark and Hadoop ecosystems. The role includes building and optimizing Neo4j graph database solutions, writing Cypher queries, and creating data pipelines for large-scale data processing.

You will collaborate with architects, data scientists, and business stakeholders to ensure data quality, governance, and security standards are maintained, while participating in code

Qualifications

• 6-10 years of 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.
• Experience loading data into Neo4j using PySpark Parallel Loader.
• Understanding of data modeling and ETL/ELT processes.

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 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.

Skills

PySpark

Hadoop

Cypher

Graph databases

data pipelines

data modeling

ETL/ELT

distributed computing

performance tuning

data quality governance

Tools

Neo4j

Job description

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.