Mahesh Behera
Principal Software Engineer at The Apache Software Foundation
Bengaluru, Karnataka, India
Summary
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Rockstar🎓
Top SchoolMahesh Behera is a Principal Software Engineer based in Bengaluru with two decades of systems and database engineering experience and a decade in senior roles shaping distributed data platforms. He currently architects large-scale data features at Microsoft and serves as an Apache Hive committer and PMC member, contributing replication fixes, timestamp handling, and test coverage to the widely used Apache Hive project. Previously he led in-memory and OLAP database design at Huawei and drove principal-level engineering at Hortonworks and Cloudera, specializing in distributed query execution, NUMA-aware optimizations, SIMD/vectorization, and replication correctness. Known for bridging deep systems optimization with production-grade distributed services, he combines low-level performance work with pragmatic platform design. Collected across open source and enterprise roles, his track record includes ensuring data fidelity in replication paths and retaining ownership metadata—small details that matter at scale.
9 years of coding experience
18 years of employment as a software developer
BE, Information Technology, BE, Information Technology at National Institute of Technology Karnataka
Github Skills (11)
javas10
replication10
back-end-development10
apache-hive10
java10
data-engineering9
sql9
databases8
sql-database8
database8
relational-databases8
Programming languages (2)
Github contributions (5)
apache/hive
Feb 2018 - Jul 2022
Apache Hive
Role in this project:
Back-end Developer
Back-end DeveloperContributions:131 reviews, 72 commits, 147 PRs in 4 years 5 months
Contributions summary:Mahesh's contributions focus on enhancing the Apache Hive codebase by addressing replication-related issues, including supporting REPL STATUS with the WITH clause and correcting a bug where REPL LOAD was creating staging directories in incorrect locations. They also resolved issues related to reading timestamp data types via HiveServer2 and improved data handling during imports. Additionally, the user worked on ensuring Hive replication retains the owner information in replicated tables and on the creation of test cases.
flinksqlapachebig-dataspark
maheshk114/spark
Jul 2023 - Apr 2024
Apache Spark - A unified analytics engine for large-scale data processing
Contributions:20 pushes, 2 branches in 9 months
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