Saumya S is an experienced Big Data Engineer with a strong background in data engineering and software development. At Johnson & Johnson, Saumya S handles data imports, transformations, and loading using technologies such as Hive, MapReduce, and Spark, alongside AWS services like EC2 and S3. Prior experience includes positions at Ally Bank, where Saumya S developed Kafka producers and Spark applications, and at Triwest Healthcare, focusing on Spark clusters with Azure Databricks. Saumya S has a solid foundation in software engineering from roles at Nitchbit and Adobe, involving backend configuration using Spring frameworks, Core and Advanced Java, and data handling with Hadoop and Sqoop. Overall, Saumya S demonstrates a comprehensive skill set in big data technologies and software engineering practices across multiple industries.
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