Akash Sonone

Assisted in developing and maintaining large-scale data processing pipelines using Sqoop, Hive, Apache Spark and Hadoop, enabling efficient data ingestion, transformation, and analysis, resulting in improved data accessibility and reduced processing time by 30%. Conducted performance tuning and optimization of ETL jobs to handle large volumes of data efficiently and meet service level agreements (SLAs). Participated in data ingestion and transformation activities, ensuring data accuracy and consistency. Optimized query performance and data processing time by fine-tuning SQL queries, partitioning data, and leveraging indexing techniques to generation of Extracts through creation of Data Marts (SQL scripts and procedures). Responsible for critical batch processes of the primary legacy system and the development and support of the BAU reporting. Collaborated with cross-functional teams to identify and resolve data-related issues and bottlenecks.