Saumitra Shahapure
About Saumitra Shahapure
Saumitra Shahapure is a Software Engineer with a focus on scalable and reliable distributed systems. He currently works at Dremio and has a diverse background in software engineering across several prominent companies, including Meta and Adobe Systems.
Work at Dremio
Saumitra Shahapure has been working as a Software Engineer at Dremio since 2023. His role focuses on building scalable and reliable distributed systems. Dremio is known for its data lake engine that simplifies data access and analysis. Shahapure's contributions are part of a remote team based in Santa Clara County, California.
Previous Experience at Meta
Before joining Dremio, Saumitra Shahapure worked at Meta as a Software Engineer from 2019 to 2023. During his four years at Meta, he contributed to various projects that required expertise in software development and system architecture. His experience at Meta enhanced his skills in building complex systems.
Career at HERE Technologies
Saumitra Shahapure served as a Software Engineer at HERE Technologies from 2016 to 2019. His three-year tenure in the Berlin Area, Germany, involved developing software solutions that supported location-based services. This role contributed to his understanding of data-driven technologies.
Educational Background
Saumitra Shahapure holds a Bachelor of Engineering (BE) in Information Technology from Savitribai Phule Pune University, where he studied from 2005 to 2009. He further advanced his education by obtaining a Master of Engineering (ME) in Computer Science and Automation from the Indian Institute of Science (IISc). This academic background laid the foundation for his career in software engineering.
Expertise in Distributed Systems
Saumitra Shahapure has extensive experience in building large-scale distributed data analytics platforms. He has worked on Big Data systems both as a developer and as a user, which has equipped him with a comprehensive understanding of the challenges and solutions in this field. His expertise is particularly valuable in the context of modern data engineering.