Thejdeep Gudivada
Senior Software Engineer at LinkedIn
San Francisco, California, United States
Summary
🤩
Rockstar🎓
Top SchoolThejdeep Gudivada is a Senior Software Engineer in San Francisco with 12 years of experience building scalable systems, currently focused on Spark and big data platforms at LinkedIn. He has a strong backend pedigree demonstrated by substantive contributions to Apache Spark’s core—improving UI, shuffle service logging/namespace, concurrent eviction handling, and speculative-task metrics—highlighting deep knowledge of distributed execution and performance monitoring. Earlier roles at Verizon Media and Yahoo expanded his expertise into client-side infrastructure and React state migrations, while internships at Cisco and Flipkart sharpened his systems and web-performance skills. He holds a B.Tech from NIT Karnataka and an MS from UC Irvine, and is driven by a daily curiosity to learn and collectively build impactful software.
12 years of coding experience
3 years of employment as a software developer
University of California, IrvineB.Tech, Computer Science, 3.6/4, B.Tech, Computer Science, 3.6/4 at National Institute of Technology Karnataka
Telugu, Kannada, Hindi, English
Stackoverflow
13reputation
543reached
0answers
2questions
Github Skills (9)
scala10
javas10
big-data10
spark10
java10
google-play6
android6
android-fragments6
sql4
Programming languages (6)
Github contributions (5)
apache/spark
Nov 2021 - Jan 2023
Apache Spark - A unified analytics engine for large-scale data processing
Role in this project:
Back-end Developer
Back-end DeveloperContributions:43 reviews, 3 commits, 11 PRs in 1 year 2 months
Contributions summary:Thejdeep primarily contributed to Apache Spark's core functionality, focusing on improving the user interface, enhancing the shuffle service, and addressing core issues related to application eviction and speculative execution metrics. Their work included fixing UI log messages, adding namespacing for the external shuffle service logs, implementing a solution to handle concurrent eviction of applications, and adding new stage-level metrics for speculative tasks. These contributions demonstrate expertise in Spark's internal architecture and performance monitoring capabilities.
analyticspythondata-processingsqlapache
thejdeep/Dashboard
Dec 2013 - Feb 2014
Contributions:86 commits in 2 months
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