Sumanth Muvva

About Sumanth Muvva

As a Data Engineering expert with a solid foundation in healthcare and finance domains, I leverage data and cloud technologies to solve complex problems and deliver value. I hold a Master of Science in Computer Science from Indiana University Bloomington, specializing in machine learning, big data, cloud computing, and distributed systems. I have over 3 years of professional experience as a Data Engineer at UnitedHealth Group.At UnitedHealth Group, I designed, developed, and deployed scalable data pipelines using Azure, AWS, Python, Airflow, Teradata, and SQL. I managed ETL pipelines handling over 180 million rows, implementing Data Lakehouse architecture on Azure Synapse, saving $10,824 annually. I developed an Automated Reconciliation Framework using Presto and PySpark, reducing data reconciliation times by 50%.I am proficient in Data Engineering, Data Modeling, and Data Warehousing, with a strong background in analytics. My technical skills include Apache Spark, Hadoop, AWS, Hive, Python, Java, Scala, Linux, and data formats like Parquet and Delta Tables. Additionally, I have experience with Databricks, Apache Kafka, Amazon Redshift, Power BI, Tableau, Grafana, and Snowflake.At Indiana University, I worked on modernizing data infrastructure by migrating SQL Server pipelines to AWS and Azure cloud. I optimized Hive query performance with Apache Spark, reducing query latency from minutes to under 30 seconds, and developed CI/CD pipelines for Azure data models, halving deployment times. I also automated Azure resource provisioning using Terraform, minimizing configuration errors by 95%.I am eager to learn new tools and collaborate with diverse teams. I am actively seeking full-time opportunities as a Data Engineer or Data Analyst to apply my skills to impactful projects.In summary, my experience as a Data Engineer includes technical proficiency, innovative problem-solving, and impactful project leadership. I aim to expand my knowledge and contribute to innovative projects with meaningful impact.Skills: Data Engineering, Data Modeling, Apache Spark, Extract Transform Load (ETL), ELT, Hadoop, Amazon Web Services (AWS), Hive, Python (Programming Language), Java, Scala, Linux, XML, Parquet, Delta Tables, Big Data, Data Warehousing, SQL, Databricks, Apache Kafka, Amazon Redshift, Machine Learning, PySpark, Microsoft Power BI, Tableau, Grafana, Apache Airflow, Snowflake, PostgreSQL, REST APIs, Data Visualization, Analytics, Data Governance, Microsoft SQL Server, SSIS, Data Integration, Solution Architecture.Email: m••••••••@gmail.com

Experience

1. Senior Data Engineer

   Microsoft

   Jul 2024 — Present · Redmond, WA, US

   Designed and owned Azure data pipelines integrating 10+ data sources, feeding 18+ global enterprise reports.• Owned end-to-end architecture and governance of 4 Microsoft Fabric workspaces and analytics reports, with strict security, RBAC, and SLA compliance.• Migrated 118+ pipelines from SSIS/Synapse to Microsoft Fabric (OneLake, Lakehouse), completing validation in 6 weeks with 99.9% data accuracy.• Led a team of 7 engineers delivering 2 mission-critical financial modules used by 50+ senior stakeholders.• Replaced 200+ SQL stored procedures with Spark-based transformations, improving scalability and reducing technical debt by 40%.• Built predictive models using PySpark and Jupyter, achieving 89% forecast accuracy for Azure consumption trends.• Optimized Spark pipelines processing 1.5B+ records/day, reducing runtime by 60% through partitioning and storage tuning.• Implemented Fabric Deployment CI/CD pipelines using Git and Azure DevOps, reducing deployment cycles by 40% and improving reliability.

Education

• Indiana University Bloomington

  Master of Science - MS, Computer Science

• KL University

  Bachelor of Science - BS, Computer Science