Saumitra Shahapure
Software Engineer at Dremio
San Francisco Bay Area United States
Summary
👤
Senior🎓
Top SchoolSaumitra Shahapure is a software engineer with 11 years of experience designing and operating large-scale distributed data analytics platforms, currently building infrastructure at Dremio in the San Francisco Bay Area. He has deep, hands-on expertise across Spark, Presto, Hive, and Hadoop ecosystems, having worked on query planning, optimization, and platform reliability at Meta and contributed backend improvements to the widely used Presto project. His background spans end-to-end data platform work—from autoscaling Hive/Spark clusters and cost-optimizing query engines to building data pipelines and visualization tools for search and integrity analytics. Notable projects include row-level access enforcement for Spark at Meta and an adaptive Hive/Spark query redirection system that cut costs and improved reliability at Vizury. He blends pragmatic engineering with a research mindset from an ME in Computer Science, routinely improving cost models and planner stats to make large-query workloads more efficient. Colleagues rely on him to navigate complex distributed-system tradeoffs and deliver scalable, production-grade solutions.
10 years of coding experience
11 years of employment as a software developer
ME, Computer Science and Automation, ME, Computer Science and Automation at Indian Institute of ScienceSavitribai Phule Pune University
English, Hindi, Marathi
Github Skills (9)
javas10
sql-query10
presto10
sql10
java10
big-data9
data-set8
data-model8
price-data8
Programming languages (6)
Github contributions (5)
prestodb/presto
Mar 2019 - Jun 2021
The official home of the Presto distributed SQL query engine for big data
Role in this project:
Back-end Developer
Back-end DeveloperContributions:15 reviews, 7 commits, 11 PRs in 2 years 4 months
Contributions summary:Saumitra's commits focus on enhancing the Presto query engine's functionality and cost optimization capabilities. They implemented improvements to the `split` function, enabling it to handle empty string delimiters. Furthermore, the user added crucial stats and cost rules for the `SampleNode` and `IntersectNode`, improving the accuracy of cost-based query optimization within the system. These changes enhance the engine's efficiency and optimization strategies.
distributed-sqlquerybigdataquery-enginesql
ssaumitra/presto
Jun 2019 - Mar 2022
The official home of the Presto distributed SQL query engine for big data
Contributions:77 pushes, 22 branches in 2 years 9 months
flink-sqljdbchbasebigdatabig-data
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