Krishna Gopal
Software Engineer at Pinterest
New York, New York, United States
Summary
🤩
Rockstar🎓
Top SchoolKrishna Gopal is a software engineer based in New York with nine years of experience building full-stack data and infrastructure tools, currently developing at Pinterest. He has a solid background in data engineering—optimizing Spark applications and integrating tooling with Slack for operational feedback—and has shipped UI and backend features for Querybook, a notable open-source big-data query notebook. His experience spans internships at Facebook and FedEx, a Kleiner Perkins fellowship, and hands-on teaching roles at USC and tech camps, showing a blend of production engineering and mentorship. He excels at translating data-platform needs into user-facing features like query search and templating, and at automating CI/CD and containerized deployments. Comfortable across front-end, back-end, and data systems, he brings practical performance-focused problem solving to large-scale analytics workflows. Beyond code, he pairs engineering craft with a track record of operationalizing developer tools that improve team velocity.
9 years of coding experience
1 year of employment as a software developer
Bachelor of Science - BS Computer Engineering and Computer Science, Bachelor of Science - BS Computer Engineering and Computer Science at University of Southern CaliforniaBrookfield Central High School
Github Skills (16)
elasticsearch10
typescript10
elasticsearchquery10
typescripts10
aws-elasticsearch10
react10
typescript-types10
elasticsearch-api10
amazon-elasticsearch10
flask-ask9
flask9
python9
backend9
front-end-development9
back-end-development9
Programming languages (5)
Github contributions (5)
pinterest/querybook
Aug 2021 - Jul 2022
Querybook is a Big Data Querying UI, combining collocated table metadata and a simple notebook interface.
Role in this project:
Full-stack Developer
Full-stack DeveloperContributions:102 reviews, 12 commits, 35 PRs in 10 months
Contributions summary:Krishna's contributions primarily focused on enhancing the UI and backend functionalities of the "Querybook" application. They implemented features to filter tables by query engines, adding new components and modifying existing ones. They also introduced a "latest_partition" template function, improving query templating capabilities. Furthermore, the user implemented query search functionality, demonstrating proficiency in integrating search features and addressing related UI and backend issues.
queryinganalyseschartingflasknotebook
kgopal492/querybook
Jun 2022 - Apr 2024
Querybook is a Big Data Querying UI, combining collocated table metadata and a simple notebook interface.
Contributions:44 pushes, 19 branches in 1 year 10 months
queryingnotebooksqlbig-dataspark
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