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Spark to enable efficient indexing, querying, and retrieval of data\n Optimize and tune Spark jobs for performance and scalability, ensuring efficient data processing and indexing in Elasticsearch\n Implement data transformations, aggregations, and computations using Spark RDDs, DataFrames, and Datasets, and integrate them with Elasticsearch\n Develop and maintain scalable and fault-tolerant Spark applications, adhering to industry best practices and coding standards\n Troubleshoot and resolve issues related to data processing, performance, and data quality in the Spark-Elasticsearch integration\n Monitor and analyze job performance metrics, identify bottlenecks, and propose optimizations in both Spark and Elasticsearch components\n Ensure data quality and integrity throughout the data processing lifecycle\n Design and deploy data engineering solutions on OpenShift Container Platform (OCP) using containerization and orchestration techniques\nRequirements\nBachelor's or Master's degree 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