Open to opportunities

Krishna Sathvik
Mantripragada

Senior Data Engineer — Azure · Databricks · Kafka · Snowflake

Senior Data Engineer with 6+ years building scalable data infrastructure and analytics solutions across healthcare and enterprise environments. Skilled in Azure, AWS, Python, and the modern data stack (Databricks, Synapse, Power BI). Proven track record in delivering predictive analytics, automated reporting, and actionable insights that improve operational efficiency, forecasting accuracy, and decision-making across large-scale data ecosystems.

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Skills

Data Engineering & ETL

dbt, Azure Data Factory, Airflow, Data Orchestration, ETL Pipelines

AI & ML

Predictive Modeling, Forecasting, Anomaly Detection, Azure Machine Learning

Cloud & Databases

Azure, AWS, Snowflake, Redshift, BigQuery, PostgreSQL, MySQL, Oracle

DevOps & Automation

Workflow Automation, CI/CD for Data, Data Quality Monitoring

BI & Visualization

Power BI, Tableau, Looker

Programming Languages

SQL, Python, R

Experience

Data Engineer | Walgreens Boots Alliance – Chicago, IL

Feb 2022 – Present

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 Python and SQL 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

Analytics Engineer | CVS – Denton, TX

Oct 2020 – Dec 2021

Designed and deployed Python and SQL-based 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 SQL queries and migrated business logic to Python scripts, 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

Data Science Intern | McKesson – Denton, TX

Mar 2020 – Sep 2020

Developed Python 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

Software Developer | Inditek Pioneer Solutions – Hyderabad, India

Jan 2019 – Dec 2019

Built scalable backend APIs using Python and 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