Graph Data Engineer- C11 - PUNE

Job Description

Responsibilities:

• Neo4j expertise: Proven experience with Neo4j, including its core concepts, Cypher query language, and best practices. 
• Designing and implementing graph database solutions: This includes creating and maintaining graph schemas, models, and architectures. Designing, developing, and deploying graph-based solutions using Neo4j. This includes defining data models, creating nodes, relationships, and properties, and implementing Cypher queries to retrieve and manipulate data. 
• Migrate data from relational or other databases into Neo4j.
• Optimizing Cypher queries for performance, ensuring efficient data retrieval and manipulation. This may involve indexing, query optimization techniques, and understanding graph database performance characteristics. 
• Familiarity with graph theory, graph data modeling, and other graph database technologies
• Developing and optimizing Cypher queries
• Integrating Neo4j with BI and other systems

Good to have:

• Develop Spark applications using Scala or Python (Pyspark) for data transformation, aggregation, and analysis.
• Develop and maintain Kafka-based data pipelines: This includes designing Kafka Streams, setting up Kafka Clusters, and ensuring efficient data flow.
• Create and optimize Spark applications using Scala and PySpark: They leverage these languages to process large datasets and implement data transformations and aggregations.
• Creating and maintaining documentation for system architecture, design, and operational processes

Proficiency in: 

• Deep hands-on expertise into building Neo4j Graph solution
• Hadoop ecosystem big data tech stack (HDFS, YARN, MapReduce, Hive, Impala)

Good to have:

• Spark (Scala, Python) for data processing and analysis.
• Kafka for real-time data ingestion and processing.
• ETL processes and data ingestion tools 
• Hands-on expertise in Pyspark, Scala, Kafka