Suhas Yogeshwara

Implemented 3+ ETL pipelines and CI/CD automation for healthcare interoperability (FHIR). Enhanced schema governance and validation, ensuring compliance for sensitive medical data. Contributed to cloud-ready pipelines integrating S3-compatible storage and Airflow. Collaborated with global researchers, strengthening data-sharing reliability.

Collected, cleaned, and analyzed 100k+ records using Python & SQL, improving data accuracy by 20%. Designed interactive Power BI dashboards for campaign performance and user activity. Automated validation & reporting workflows, cutting prep time by 30% (4+ hrs/week). Partnered with product managers to turn data insights into product enhancements, driving a 12% increase in user retention.

Built and deployed 5+ ETL pipelines in Airflow for multi-source ingestion into a cloud lakehouse, processing 1M+ records/week with 99% uptime. Optimized SQL queries, reducing runtime by 25% and improving downstream analytics speed. Automated validation scripts to fix 100+ data quality issues, reducing reporting errors by 15%. Integrated data flows with AWS S3 & Redshift, enabling scalable storage and real-time analytics.

Built ETL workflows to process 500+ hours of unstructured voice data using Python, Spark & Beam. Deployed ML pipelines on Kubernetes, scaling processing for datasets 10× larger. Created automated testing workflows, reducing data processing errors by 30%. Collaborated with a team of 4 researchers to deliver project milestones ahead of deadlines, improving project efficiency and stakeholder satisfaction.