Graph Data Engineer

As a candidate for the position, here is a summary of the job description: Role Overview: - You should have expertise in Neo4j, including its core concepts, Cypher query language, and best practices. - Responsible for designing and implementing graph database solutions, creating and maintaining graph schemas, models, and architectures. - Your role will involve migrating data from relational or other databases into Neo4j and optimizing Cypher queries for performance to ensure efficient data retrieval and manipulation. - Essential to have familiarity with graph theory, graph data modeling, and other graph database technologies. - Developing and optimizing Cypher queries, as well as integrating Neo4j with BI and other systems. Key Responsibilities: - Experience in developing Spark applications using Scala or Python (Pyspark) for data transformation, aggregation, and analysis. - Develop and maintain Kafka-based data pipelines. - Create and optimize Spark applications using Scala and PySpark. - Proficiency in the Hadoop ecosystem big data tech stack (HDFS, YARN, MapReduce, Hive, Impala). - Hands-on expertise in building Neo4j Graph solutions, Spark (Scala, Python) for data processing and analysis, Kafka for real-time data ingestion and processing, ETL processes, data ingestion tools, Pyspark, Scala, and Kafka. Qualifications Required: - Experience in Neo4j, Cypher query language, and graph database technologies. - Proficiency in developing Spark applications using Scala or Python (Pyspark). - Knowledge of Kafka-based data pipelines and the Hadoop ecosystem big data tech stack. - Hands-on expertise in building Neo4j Graph solutions, Spark, Kafka, ETL processes, and data ingestion tools. If you require a reasonable accommodation due to a disability to use search tools or apply for a career opportunity, please review Citi's Accessibility information. Additionally, you can refer to Citis EEO Policy Statement and the Know Your Rights poster for more details.,