Afresh, the AI platform for grocery, began by tackling the most complex problem in the industry: fresh, and has evolved into the core AI platform for grocers.
By leveraging proprietary AI designed for high-volatility environments, we empower partners like Albertsons, Meijer, and Wakefern to drive smarter decisions across their entire enterprise.
Following record-breaking 70% revenue growth in 2025, we have scaled to 6 enterprise-grade solutions, with solutions live in over 10% of the U.S. grocery market. Our platform now orchestrates billions of decisions from the store floor to the distribution center and prevented over 200 million pounds of food waste last year alone.
If you're looking for a role where your work directly translates into massive scale and social good, and you want to be part of the team that defines how the world eats, there is no better time to join us.
About the Role
As a Staff Data Engineer, on the Distribution Center (DC) Solutions team, you’ll play a technical lead role in building and scaling the data integrations needed to support our suite of DC products. You will design and implement ETLs that reliably process large volumes of customer-provided data and build tools/improve the platform to make customer integrations faster, more accurate, and more scalable. Your work will have a direct and visible impact on our ability to onboard customers more easily and quickly and power our machine learning grocery solution.
What You’ll Do
- Engineering & Data Pipelines: Design, build, and optimize robust ETLs using PySpark and DBT to process large-scale customer datasets while developing tools and frameworks to streamline data integrations and improve scalability.
- Technical Leadership & Strategy: Define the technical vision for DC data architecture, mentor engineers, and manage external contractors to ensure the team delivers high-quality, practical solutions for current and future needs.
- Cross-functional Collaboration: Partner with product, engineering, and applied science teams to scope work and deliver data solutions that address real-world challenges in customer data quality and product feature requirements.
What Makes You a Great Fit
We encourage all highly-qualified candidates to apply, even if they don’t meet every listed qualification.
- Significant experience designing and maintaining ETLs that process large-scale datasets.
- Proficiency with Python, PySpark, SQL, and experience working on platforms/tools like Databricks, Snowflake, or DBT.
- 2+ years experience in a technical lead role (e.g. Tech Lead or Engineering Manager), with a willingness to mentor and help others grow.
- Strong problem-solving skills and the ability to work with ambiguous or incomplete requirements to deliver concrete, impactful solutions.
- A focus on practical outcomes—you're skilled at balancing technical rigor with the need to get things done.
- Experience working directly with complex, unclean datasets and finding innovative ways to process and analyze them.
- A knack for identifying areas where tooling or automation can simplify workflows and reduce manual effort.
- Excellent communication skills—you’re able to explain your ideas clearly to both technical and non-technical audiences.
We’re looking for someone who thrives on tackling complex data problems and takes pride in building systems that work seamlessly at scale. If that sounds like you, we’d love to hear from you!
This position is not eligible for immigration sponsorship
Salary Range in US: $168K - $273K
At Afresh, our mission to eliminate food waste starts with investing in our people. We provide a comprehensive support system designed to help you do your best work while maintaining a healthy, balanced life.
- Comprehensive Health & Wellness: Comprehensive medical, dental, and vision coverage for you and your family, with the majority of premiums covered by Afresh. We also provide dedicated mental health support and counseling services.
- Invested in Your Future: Competitive base salary, meaningful equity (U.S. employees), and a 401(k) program with a generous company match.
- Flexible & Modern Workspace: Whether you work from home or a local office, we support your setup with a home office stipend and "Coworking Wallets" for flexible workspace access.
- Growth-Obsessed Culture: We believe in continuous learning. Every employee receives an annual professional development budget to master new skills and grow their career at Afresh.
- Holistic Monthly Stipends: Beyond your paycheck, we provide monthly stipends for "Betterment" (wellness/lifestyle) and telecommunications to ensure you have what you need to thrive.
- Time to Recharge: Flexible paid time off to take the time you need to recharge.
About Afresh
Founded in 2017, Afresh is using AI to tackle the #1 solution to curb climate change: reducing food waste. By building AI specifically for the intricacies of grocery—from the fresh perimeter to the center store—we help grocers minimize waste and maximize sales.
Afresh sits at an incredible intersection of positive social impact, rocket ship financial growth, and cutting-edge technology. Our best-in-class AI research has been published in top journals, including ICML, and our investors include Al Gore’s Just Climate, former Whole Foods Market CEO Walter Robb, and Eric Schmidt's Innovation Endeavors.
Grocery is the past, present, and future of our food system – the waste we create today will impact our planet for years to come. Join us as we continue to build a vibrant, diverse, and inclusive team that embodies our company’s values of proactivity, kindness, candor, and humility.
Afresh provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, national origin, age, disability, genetics, sexual orientation, gender identity/expression, marital status, pregnancy or related condition, or any other basis protected by law.
Here at Afresh, many of our employees work remotely provided that they reside in one of the following states: AL, AR, CA, CO, FL, GA, IL, KY, MA, MI, MT, MO, NV, NJ, NY, NC, OR, PA, TX, WA, UT, VA, WI.
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