Tejas Ajmera
Senior Software Engineer at LinkedIn
Mountain View, California, United States
Summary
🤩
Rockstar🎓
Top SchoolTejas Ajmera is a Senior Software Engineer with over a decade of experience building scalable web front-ends and data visualization platforms, currently driving front-end infrastructure for LinkedIn’s Big Data org. He leads development of a platform for anomaly detection, root-cause analysis and forecasting used across teams, while improving developer tooling and shipping velocity through mentoring and craftsmanship. His background spans reusable charting libraries for global, client-facing insights and earlier full-stack product work at FactSet, including C++ middle-tier services and AngularJS web apps. An active open-source contributor, he has enhanced the Apache Pinot realtime OLAP UI with routing, performance stats integration and lightweight PubSub support—bridging production-grade telemetry with usable interfaces. Based in Mountain View, he pairs a Georgia Tech MS in CS with a practical focus on scalable, observable front-end systems that make data actionable.
5 years of coding experience
9 years of employment as a software developer
Bachelors of Engineering Computer Engineering, Bachelors of Engineering Computer Engineering at D.J.Sanghvi College Of EngineeringMasters of Science Computer Science, Masters of Science Computer Science at Georgia Institute of Technology
English, Hindi, Marathi, Gujarati
Github Skills (7)
emberjs10
javascript10
front-end-development10
api9
html9
css9
apim9
Programming languages (1)
Github contributions (3)
apache/pinot
Nov 2020 - Feb 2021
Apache Pinot - A realtime distributed OLAP datastore
Role in this project:
Front-end Developer
Front-end DeveloperContributions:60 reviews, 14 commits, 14 PRs in 3 months
Contributions summary:Tejas primarily contributed to the front-end development of the Apache Pinot real-time datastore. Their work involved refactoring components for detection health and stats, including moving static HTML inside the component and optimizing code. They also built new subroutes for exploring different anomaly types and integrated the Performance Stats API into the front-end. Furthermore, they added support for a lightweight PubSub system and added the filtering support to the table components used in the entity monitoring section of the app.
realtimedata-streamolapapachedatastore
tejasajmera/incubator-pinot
Oct 2020 - Feb 2021
Apache Pinot (Incubating) - A realtime distributed OLAP datastore
Contributions:50 pushes, 15 branches in 3 months
incubatingrealtimeolapapachedatastore
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