Garv Agarwal

I’m a data engineering and analytics professional who builds Snowflake-based data models and SQL/ETL pipelines for large-scale, multi-channel analytics in the healthcare/pharma domain. At ZS Associates, I designed a robust backend data layer for LLM-driven workflows, leveraging Snowflake models to process 5M+ monthly engagement records and enable scalable analytics reporting.

I focus on reliability and measurable impact—implementing QA/QC validation frameworks, automated pipeline triggers, and pipeline monitoring to strengthen recurring analytics workflows. I’ve also translated business KPIs into dimensional models, including mapping patient journeys and defining service episodes to identify leakage points that contributed to a 20% improvement in digital engagement analytical insights. Earlier, as an intern, I reduced pipeline runtime by 40% through query optimization and pipeline redesign, and I’ve brought additional research rigor through a ParkSmart project accepted for IEEE ICICACS 2024.