About the role
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
