Akshay Rai
Staff Software Engineer at LinkedIn
Mountain View, California, United States
Summary
🤩
Rockstar🎓
Top SchoolAkshay Rai is a Staff Software Engineer in Mountain View with 11 years of experience building and operating big data and distributed systems at LinkedIn, currently working on Apache Trino. He has led engineering efforts on operational intelligence for Hadoop and Spark—open-sourcing and steering Dr. Elephant—and contributed backend fixes and schema improvements to high-profile projects like Apache Pinot. Comfortable across Java-based server systems, data transformation and real-time OLAP engines, he combines hands-on implementation with testing and documentation discipline. His background includes a Computing Systems master’s from Georgia Tech and a knack for turning cluster-level performance heuristics into actionable tooling for large-scale data platforms.
12 years of coding experience
6 years of employment as a software developer
Physics, Chemistry, Mathematics and Statistics, Physics, Chemistry, Mathematics and Statistics at Mahatma Gandhi Memorial College, UdupiMaster's degree, Computing Systems, Master's degree, Computing Systems at Georgia Institute of TechnologyBachelor of Technology (B.Tech.), Computer Science & Engineering, Bachelor of Technology (B.Tech.), Computer Science & Engineering at National Institute of Technology Karnataka
Kannada, Tulu, Hindi, English
Github Skills (15)
javas10
apache-spark10
api10
hadoop10
back-end-development10
apidoc10
java10
integrations9
emailjs9
testing9
data-structure9
database-design9
e-mail9
data-structures9
performance-tuning9
Programming languages (3)
Github contributions (5)
linkedin/dr-elephant
Sep 2014 - Sep 2019
Dr. Elephant is a job and flow-level performance monitoring and tuning tool for Apache Hadoop and Apache Spark
Role in this project:
Back-end Developer
Back-end DeveloperContributions:3 releases, 76 commits, 161 PRs in 5 years 1 month
Contributions summary:Akshay contributed to the development of Dr. Elephant, a performance monitoring and tuning tool for Hadoop and Spark. The contributions focus on implementing and testing a job queue limit heuristic, which detects tasks nearing their queue limits. The changes involve Java code modifications, including creating a new heuristic class and writing associated test cases, indicating a focus on back-end system logic and testing. Additionally, the user updated help pages related to performance tuning.
apache-hadoopapache-sparkperformance-monitoring
apache/pinot
Sep 2018 - Oct 2020
Apache Pinot - A realtime distributed OLAP datastore
Role in this project:Back-end Developer
Back-end DeveloperContributions:16 reviews, 234 commits, 521 PRs in 2 years 1 month
Contributions summary:Akshay primarily focused on back-end development tasks, including bug fixes, code refactoring, and database schema changes within the Apache Pinot project. Their work involved trimming whitespaces in emails, migrating data from comma-separated strings to a set data structure, and adding support for CC and BCC recipients. These contributions highlight expertise in Java programming, data transformation, and API development.
apache-pinotolapjava
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