On Peloton's leaderboard team I work with services that receive more than 2 billion requests per day. Currently I am re-architecting our backend to make our services more resilient to surges in traffic at the beginning of large fitness classes and I am improving the scalability of Peloton's Apple Watch integration. I work with kubernetes, kafka, redis, dynamodb, postgres, argo, datadog, python, kotlin, etc. Some highlights have been:

• Building and rolling out the micro-service that ingests all of Peloton's leaderboard data.
• Testing, scaling, and maintaining the leaderboard for Peloton's Ride to Greatness, an annual class where cyclers compete in teams.
• Making it to semi-finals of the software org's ping pong tournament.

I mentored students as they completed a project to design a database schema for an application of their choice. Together we thought through how to design schemas for applications like Facebook, or Yelp. When I was originally a student in the class, I designed a database for an application that helped multi-state residents choose which U.S. state they should vote in to maximize impact in national elections.

Have you ever wanted to buy the outfit of a TV or movie character? TheTake lets you shop shows and movies directly from your TV--their API powers LG TV's "Who What Where" feature. As an intern I built a generalized system to scrape data from clothing retailers' websites. The data I collected allowed the company to expand their database of clothes that could be matched to those in TV and movies scenes.