- Design, develop, and implement Spark Scala applications and data processing pipelines to process large volumes of structured and unstructured data
- Integrate Elasticsearch with Spark to enable efficient indexing, querying, and retrieval of data
- Optimize and tune Spark jobs for performance and scalability, ensuring efficient data processing and indexing in Elasticsearch
- Collaborate with Data Engineers, data scientists, and other stakeholders to understand requirements and translate them into technical specifications and solutions
- Implement data transformations, aggregations, and computations using Spark RDDs, DataFrames, and Datasets, and integrate them with Elasticsearch
- Develop and maintain scalable and fault-tolerant Spark applications, adhering to industry best practices and coding standards
- Troubleshoot and resolve issues related to data processing, performance, and data quality in the Spark-Elasticsearch integration
Requirements * 5+ Years as
Data Engineer- 5 Years experience in Spark, Scala, Elastic Search
- Develop and maintain scalable and fault-tolerant Spark applications, adhering to industry best practices and coding standards
- Monitor and analyze job performance metrics, identify bottlenecks, and propose optimizations in both Spark and Elasticsearch components
- Stay updated with emerging trends and advancements in the big data technologies space to ensure continuous improvement and innovation
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