Hungryroot Logo

Senior Data Engineer

💰 $151k-$189k

Job Description

About Us

Hungryroot is using AI to build the most consumer-centric food and wellness company to ever exist. We act as your personal assistant for healthy living—getting to know your goals, lifestyle, and budget, and recommending and delivering healthy groceries, easy recipes, and essential supplements for you and your family.

It’s the easiest way to eat healthy, achieve your goals, save time, and discover new foods. We believe food is the foundation of health, convenience should not mean compromise, and that everyone is unique in how they eat and live. That’s why we’re building a future in which healthy living is both easy and enjoyable.

Hungryroot is a distributed team of top talent across 28+ U.S. states. While we have a headquarters in New York City, our remote-first culture emphasizes collaboration, team-building, and flexibility. Expect regular virtual team events, strong ownership and accountability, and an annual company retreat.

About the Role

We’re looking for a Senior Data Engineer to be a part of our growing Data team. You’ll be responsible for working directly on the data pipelines and systems that create our Hungryroot Analytics data model used to inform financial decision making, product development, inventory management and more.

As a member of the team, you will work collaboratively with Analysts across many departments and your Data Engineering peers to build, deploy, and maintain data pipelines that power our Analytics data model. You will be responsible for data model design, developing and deploying pipelines, and setting the example of code quality and value across the Data Engineering team.

This role will join Hungryroot’s Data Engineering team and you’ll report directly to our Senior Director, Data Platform & Governance. In this role, you will work closely with Analysts at Hungryroot to improve our Analytical data model and unlock our Analyst’s potential to make broad impacts at Hungryroot. You will set an example in the Data Engineering team as a strong pipeline developer, communicator, and teacher for your Data Engineering peers.

Come join our team, apply your passion for data and have fun!

Responsibilities

  • Develop pipelines in Spark (Python) in the Databricks Platform
  • Build cross-functional working relationships with business partners in Food Analytics, Operations, Marketing, and Web/App Development teams to power pipeline development for the business
  • Ensure system reliability and performance
  • Deploy and maintain data pipelines in production
  • Set an example of code quality, data quality, and best practices
  • Work with Analysts and Data Engineers to enable high quality self-service analytics for all of Hungryroot
  • Investigate datasets to answer business questions, ensuring data quality and business assumptions are understood before deploying a pipeline

Qualifications

  • 5+ years of experience in ETL development and data modeling
  • 5+ years of experience in Python
  • 2+ years of experience working with the Databricks Platform
  • Experience with Spark
  • Excellent problem-solving skills and the ability to translate business problems into practical solutions

Perks & Benefits

  • Remote-first: work from home, work from our NYC office, work from anywhere in the U.S. - you decide!
  • Equity
  • Unlimited vacation policy
  • Universal paid parental leave
  • Monthly Hungryroot credit for delicious, healthy groceries
  • Comprehensive health, vision, dental, and life insurance
  • 401k with Company Match
  • A work from home stipend to support your initial home-office setup

Expected Pay Range

$151,000-$189,000

#LI-REMOTE

The employer will not sponsor applicants for work visas.

Our mission to help make healthy eating easy, accessible, and joyful is better served by a diverse workplace. We are a proud Equal Opportunity Employer committed to building an inclusive workplace. We have zero-tolerance for harassment or discrimination. We do not discriminate on the basis of any protected class.

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