Ritesh Katwe

Contributed to development and maintenance of batch ETL pipelines processing ACH financial transactions (PPD, CCD, WEB entries), supporting fraud analytics and downstream risk reporting workflows. • Built ingestion workflows processing 20K+ financial transactions/day with schema validation, deduplication checks, and anomaly detection. Developed reusable data transformation and feature engineering scripts in Python and SQL to generate consistent, analytics-ready datasets. • Improved ETL performance using incremental load strategies, indexed frequently filtered columns, and eliminated redundant full-table scans. Integrated pipeline outputs with AWS S3 for scalable object storage and implemented logging and validation checks to improve pipeline reliability. • Collaborated with senior engineers, data scientists, and analysts to troubleshoot pipeline failures and improve overall data quality. Assisted in designing curated reporting tables and aggregates used by fraud analysts to monitor transaction behavior and identify potential risks