Vishwajith Shivappa
Senior Software Engineer at Google
Sunnyvale, California, United States
Summary
👤
Senior🎓
Top SchoolVishwajith Shivappa is a Senior Software Engineer based in Sunnyvale with six years of focused experience in networking, network security, and operating systems, and deep hands-on skills in Java, C, and C++. He has built scalable, production-grade infrastructure at major tech companies including Google, LinkedIn, and Uber, and contributed to high-profile open-source projects such as LinkedIn’s Brooklin—where he improved Kafka connector reliability and observability by refactoring tracking logic and adding task-restart metrics. His background spans storage and replication systems from early roles at NetApp and Nutanix to distributed streaming and monitoring at top cloud-scale organizations. Known for pragmatic low-level optimization paired with system-wide thinking, he thrives on reducing operational complexity while improving performance and diagnostics. He blends academic grounding in computer science with practical engineering across both proprietary and open-source ecosystems, often surfacing subtle telemetry improvements that pay dividends in large deployments.
6 years of coding experience
14 years of employment as a software developer
The University of Texas at DallasB.E, Computer Science, B.E, Computer Science at Visvesvaraya Technological University
Stackoverflow
3reputation
6kreached
0answers
1question
Github Skills (9)
javas10
kafka10
data-streaming10
java10
metric9
testing8
distributed-systems7
change-data-capture7
php6
Programming languages (1)
Github contributions (4)
linkedin/brooklin
Feb 2020 - Jan 2021
An extensible distributed system for reliable nearline data streaming at scale
Role in this project:
Back-end Developer
Back-end DeveloperContributions:36 reviews, 6 commits, 12 PRs in 11 months
Contributions summary:Vishwajith made several contributions to the `linkedin/brooklin` repository, primarily focused on the Kafka connector. Their work involved removing the KafkaPositionTracker, which improved performance by replacing it with consumer group, topic, and partition reporting. The user also extended the diagnostics endpoint to report consumer groups and topic partitions, and refactored KafkaTopicPartitionStatsResponse for code reuse. Furthermore, they added a metric to monitor task restarts within the Kafka connector for better monitoring capabilities.
complex-event-processingstreamingdistributed-systemsextensiblescalability
vishwajith-s/brooklin
Feb 2020 - Jan 2021
An extensible distributed system for reliable nearline data streaming at scale
Contributions:27 pushes, 3 branches in 11 months
complex-event-processingstreamingbig-datadistributed-systemsextensible
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.