Managing The DoorDash Data Platform Data Engineering Podcast

Summary
The team at DoorDash has a complex set of optimization challenges to deal with using data that they collect from a multi-sided marketplace. In order to handle the volume and variety of information that they use to run and improve the business the data team has to build a platform that analysts and data scientists can use in a self-service manner. In this episode the head of data platform for DoorDash, Sudhir Tonse, discusses the technologies that they are using, the approach that they take to adding new systems, and how they think about priorities for what to support for the whole company vs what to leave as a specialized concern for a single team. This is a valuable look at how to manage a large and growing data platform with that supports a variety of teams with varied and evolving needs.

Announcements

Hello and welcome to the Data Engineering Podcast, the show about modern data management
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Your host is Tobias Macey and today I’m interviewing Sudhir Tonse about how the team at DoorDash designed their data platform

Interview

Introduction
How did you get involved in the area of data management?
Can you start by giving a quick overview of what you do at DoorDash?

What are some of the ways that data is used to power the business?


How has the pandemic affected the scale and volatility of the data that you are working with?
Can you describe the type(s) of data that you are working with?

What are the primary sources of data that you collect?

What secondary or third party sources of information do you rely on?


Can you give an overview of the collection process for that data?


In selecting the technologies for the various components in your data stack, what are the primary factors that you consider when evaluati