Yatish Mehta
Tech Lead, Authorization
San Francisco, California, United States
Summary
🤩
Rockstar🎓
Top SchoolYatish Mehta is a tech lead specializing in authorization and distributed systems with 14 years of experience building developer platforms and high-throughput services. Currently leading authorization at Asana, he previously scaled core backend capabilities at Opendoor and architected workflow and notification platforms at Coupa that handle millions of events and flows monthly. He combines hands-on engineering (Ruby/Rails back-end experience and microservice migrations) with people leadership, having led teams, mentored engineers, and driven performance improvements such as a 60% latency reduction in an approvals engine. His open-source work includes foundational back-end tooling like a LinkedIn profile scraper and database-focused contributions to an NSF-backed peer-review platform, highlighting a practical focus on data modeling and automation. Based in San Francisco with an MS in Computer Science, he’s known for turning complex access and workflow requirements into robust, production-ready systems that prioritize scalability and developer experience.
14 years of coding experience
13 years of employment as a software developer
Master of Science - MS Computer Science, Master of Science - MS Computer Science at North Carolina State UniversityBachelor of Engineering (B.E.) Computer Engineering, Bachelor of Engineering (B.E.) Computer Engineering at Vishwakarma Institute Of Technology
Github Skills (20)
ruby-rails10
rails10
schema-design10
webscraping10
expert10
ruby10
exp10
database-design10
db-schema10
database-schema10
data-extraction10
activerecord10
mechanize10
schema10
ruby-on-rails10
Programming languages (11)
Github contributions (5)
yatish27/linkedin-scraper
Apr 2012 - May 2016
Scrapes the public profile of the linkedin page
Role in this project:
Back-end Developer
Back-end DeveloperContributions:100 commits, 21 PRs, 51 pushes in 4 years 2 months
Contributions summary:Yatish's initial commit establishes the foundational code base for a LinkedIn profile scraper. The primary focus appears to be on extracting data from LinkedIn profiles, as indicated by the creation of core classes such as `Profile`, `Client`, and `Contact`. The code utilizes the Mechanize gem for web scraping and includes methods to retrieve profile information. The user is working on extracting information about the person's past and current companies, education, websites and groups.
linkedinscrapeslinkedin-apipublic-profilescraper
expertiza/expertiza
Sep 2014 - Nov 2015
Expertiza is a web application through which students can submit and peer-review learning objects (articles, code, web sites, etc). The Expertiza project is supported by the National Science Foundation.
Role in this project:Back-end Developer
Back-end DeveloperContributions:22 commits, 7 PRs, 6 pushes in 1 year 2 months
Contributions summary:Yatish primarily focused on database schema modifications and updates. They made changes to the `db/schema.rb` file, including adding and removing columns, modifying indexes, and updating table structures within the Rails application. Furthermore, the user addressed changes to the database setup, including a modified SQL file and changes related to the application controller. These actions suggest a focus on the application's data model and underlying database structure.
nationalpeer-reviewexpertiza-wikidjangoexpertiza
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