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DoorDash

An on-demand delivery service.

Software Engineer, Data Platform
San Francisco, CA, US
Mountain View, CA, US
Job Description / Skills Required

Come help us build the world's most reliable on-demand, logistics engine for delivery! We're bringing on talented engineers to help us create and maintain a 24x7, no downtime, global infrastructure system that powers DoorDash’s three-sided marketplace of consumers, merchants, and dashers.

About the Role

As a full stack software engineer in DoorDash’s Data Platform, your scope and impact would be enormous due to the expanding and complex business and product needs of a growing successful company. This role would have the scope and responsibility for all aspects of Data Platform.

About the Team

The Data Platform consists of multiple teams such as Data Infrastructure, Streaming Platform, ML Platform and Experimentation Platform. Our goal is to enable all of Doordash to utilize the power of data by providing a reliable, flexible and high quality Data Platform.

Some of the interesting work done in the team was published in articles such as analyzing switchback experiments (1), our evolving ML Platform (2). We help enable and unlock interesting solutions our product teams use such as marketplace decision making (3), personalized search and discovery of restaurants and food (4) etc.

What You’ll Achieve

  • You will own and be responsible for various Data Tools & Visualizations.
  • You will work alongside our Data Analysts, Data Scientists, ML Engineers and Data Infrastructure engineers to collaborate on important projects that need user interfaces and tools needed for workflows, data discovery, integrations and visualizations of various analytics.

About You

  • High-energy and confident - you’ll do whatever it takes to win
  • You’re an owner - driven, focused, and quick to take ownership of your work
  • Humble - you’re willing to jump in and you’re open to feedback
  • Adaptable, resilient, and able to thrive in ambiguity - things change quickly in our fast-paced startup and you’ll need to be able to keep up!
  • Growth-minded - you’re eager to expand your skill set and excited to carve out your career path in a hyper-growth setting
  • Desire for impact - ready to take on a lot of responsibility and work collaboratively with your team

Qualifications

  • B.S., M.S., or PhD. in Computer Science or equivalent
  • Exceptionally strong knowledge of CS fundamental concepts and OOP languages
  • 4+ years of industry experience
  • Experience architecting large-scale frontend applications
  • Mastery of the foundations of the web: vanilla JS, HTML5, CSS3
  • Deep understanding of REST principles and experience working with and implementing backend APIs
  • Experience with React/Redux, or similar frameworks
  • Experience with Java/Kotlin/Python
  • Experience with any of the “Big Data” technologies (e.g. Postgres, Redis, Elasticsearch, Snowflake, Mode, Segment, Spark etc.)
  • Experience with documentation, unit and integration testing

Nice To Haves

  • Experience building large scale, real-time applications
  • Familiar with a cloud based environment such as AWS

About Us

Founded in 2013, DoorDash is a San Francisco-based technology company passionate about transforming local businesses and dedicated to enabling new ways of working, earning, and living. Today, DoorDash connects customers with their favorite local and national businesses in more than 850 cities across the United States and Canada. By building intelligent, last-mile delivery technology for local cities, DoorDash aims to connect people with the things they care about — one dash at a time.

Our Commitment to Diversity and Inclusion

We’re committed to growing and empowering a more inclusive community within our company, industry, and cities. That’s why we hire and cultivate diverse teams of the best and brightest from all backgrounds, experiences, and perspectives. We believe that true innovation happens when everyone has room at the table and the tools, resources, and opportunity to excel. 

Links & References

  1. https://doordash.engineering/2019/09/11/cluster-robust-standard-error-in-switchback-experiments/
  2. https://doordash.engineering/2020/04/23/doordash-ml-platform-the-beginning/
  3. https://doordash.engineering/2020/03/31/supercharging-doordashs-marketplace-decision-making-with-real-time-knowledge/
  4. https://doordash.engineering/2020/06/29/doordashs-new-prediction-service/