Krishna Sathvik
Mantripragada

Process 10+ TB of healthcare retail data monthly with sub-second query performance by building scalable pipelines in Azure Databricks, Azure SQL Database, and Azure Data Factory for real-time executive dashboards

Reduce query execution costs by 22% while integrating 15+ data sources by architecting optimized ETL workflows in Azure Synapse Analytics across DEV, SIT, UAT, and PROD environments

Eliminate 30+ hours of manual work weekly and improve workflow efficiency by 30% by creating reusable automation frameworks enabling real-time analytics

Accelerate deployment cycles by 40% through CI/CD pipeline implementation in Azure DevOps, enhancing KPI tracking and data governance across healthcare analytics platforms

Designed and deployed ETL workflows processing 7+ million sales and financial records, increasing data accuracy by 16–35% and enhancing reliability of executive reporting and ML models

Automated integration workflows between on-premises systems and Oracle Cloud, reducing manual processing by 31% and enabling real-time insights in Power BI and Tableau dashboards across multiple business units

Re-engineered legacy queries and migrated business logic, improving scalability, performance, and data consistency across 8+ enterprise databases

Built Azure ML forecasting models leveraging 5+ years of historical trends, increasing budget and inventory forecast accuracy by 16% and supporting enterprise-wide resource allocation decisions

Developed scripts to clean, preprocess, and analyze 2+ million prescription and sales records, improving data readiness by 22% for downstream analytics, forecasting models, and business intelligence initiatives

Created and tested Azure ML models to predict prescription demand, achieving a 14% improvement in forecast accuracy over baseline methods and supporting supply chain and inventory management teams

Designed and deployed Tableau dashboards visualizing patient behavior and prescription trends, enabling targeted decision-making for pilot business units and improving stakeholder engagement with data insights

Partnered with data engineering team to integrate model outputs into ETL workflows, establishing automation foundations later scaled at CVS to support enterprise-wide forecasting and analytics pipelines

Built scalable backend APIs using Django, integrating 10+ user interfaces with optimized database queries processing 100K+ daily transactions, improving overall system performance by 20% and reducing downtime by 15% through critical production fixes

Developed a content aggregation and tracking system with advanced database optimization and caching, accelerating data retrieval speed by 71% and enhancing platform responsiveness for 1,000+ users