Koushik Prabhu

Developed and tested the in-house developed ETL pipeline to ingest data from various sources, including the vendor portal, email, S3 bucket, and SFTP, and create a data warehouse for analytics, forecasting, and dashboard building. Designed and implemented Python loader classes to efficiently process clinical trial studies, leveraging object-oriented programming principles, managing over 150 protocols across multiple clients. Streamlined the process of granting database access to client users through automation using Python, resulting in a 64% boost in performance. Optimized file transfer processes by automating the movement of files from vendor portals to AWS S3 with Boto3, saving over 45 hours weekly and improving team productivity. Utilized AWS services like Lambda, S3, EC2, and RDS to build scalable data processing workflows, enhancing the reliability and efficiency of data pipelines.

Led multiple projects involving data ingestion, analytics, and forecasting, collaborating with cross-functional teams to optimize data workflows and enhance decision-making capabilities. Contributed to optimizing the performance of data loader classes in the in-house ETL tool, reducing execution time from 1.35 seconds to 1.15 seconds, resulting in faster data processing.