• Build and maintain robust data pipelines that ingest, transform, and validate complex customer data using PySpark, Python, and dbt to process billions of records from customer datasets, ensuring data is accurate, reliable, and ready for downstream use. • Help improve integrations with new customers, making the process faster and more repeatable through thoughtful tooling. • Contribute to the adoption of cutting-edge AI tooling (e.g., LLM-assisted data cleaning, semantic validation, and anomaly detection). • Collaborate with product, engineering, and go-to-market teams to design and deliver data solutions for new products and features. • Identify and implement optimizations to improve ETL runtime and data processing scalability, reducing the time and effort required for integrations. • Solve real-world data quality challenges by working directly with messy, incomplete, or inconsistent customer data to extract the signal we need. • Learn and grow by pairing with other engineers, participating in design reviews, and taking on bigger and bigger projects.

Afresh is the leading AI company in fresh food—partnering with grocers like Albertsons, Wakefern, Meijer, and Stater Bros to order billions of dollars of fresh food in over 12,000 grocery departments nationwide. Following record-breaking 70% growth in 2025, we’ve expanded our platform to cover all fresh departments, launched our full store suite, and debuted DC Fresh Buying. We’re on a mission to eliminate food waste and make fresh food accessible to all. In 2025 alone our software helped save 200M lbs of food waste. 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 the future of fresh, there is no better time to join us. About the Role We’re looking for a Data Engineer who’s excited to work at the intersection of food waste, large-scale data processing, and applied AI. In this role, you’ll help shape how customer data flows through our platform, improving how we ingest, transform, and operationalize real-world datasets to drive down food waste for grocery chains. You’ll work closely with other data engineers, product engineers, and AI/ML engineers to design and implement reliable, efficient ETL pipelines and streamline how we integrate with new customers. You’ll contribute to the development of new features that support our expanding product lines. Your work will have a direct and visible impact on our ability to onboard customers more easily/quickly and power our machine learning grocery solution. What You’ll Do - Build and maintain robust data pipelines that ingest, transform, and validate complex customer data using PySpark, Python, and dbt to process billions of records from customer datasets, ensuring data is accurate, reliable, and ready for downstream use. - Help improve integrations with new customers, making the process faster and more repeatable through thoughtful tooling. - Contribute to the adoption of cutting-edge AI tooling (e.g., LLM-assisted data cleaning, semantic validation, and anomaly detection). - Collaborate with product, engineering, and go-to-market teams to design and deliver data solutions for new products and features. - Identify and implement optimizations to improve ETL runtime and data processing scalability, reducing the time and effort required for integrations. - Solve real-world data quality challenges by working directly with messy, incomplete, or inconsistent customer data to extract the signal we need. - Learn and grow by pairing with other engineers, participating in design reviews, and taking on bigger and bigger projects. Skills and Experience - 2+ years of experience building ETLs or data workflows with Python, PySpark, SQL, or similar tools. - Comfortable working with messy, incomplete, or inconsistent datasets—and turning them into something structured and usable. - Experience in identifying areas where tooling or automation can simplify workflows and reduce manual effort. - Experience or strong interest in platforms like Databricks, Snowflake, and dbt. - Strong problem-solving skills and the ability to work with ambiguous or incomplete requirements to deliver concrete, impactful solutions. - Attention to detail and pride in delivering robust, maintainable solutions. - Collaborative and communicative — you work well across teams and aren't afraid to ask questions. - Learning mindset — hungry to grow your skills and move fast. We encourage all highly-qualified candidates to apply, even if they don’t meet every listed qualification. We encourage you to apply even if you don’t meet every requirement. This position is not eligible for employer sponsorship Salary Band in Canada: $114,00 - 154,000 About Afresh Founded in 2017, Afresh is working on the #1 solution to curb climate change: reducing food waste. By combining human insight and transformative technology, we're helping grocers provide fresher food to customers at more affordable prices. 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 we've raised over $148 million in funding from investors including former co-CEO of Whole Foods Market Walter Robb and Eric Schmidt's Innovation Endeavors. Fresh 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.

• We collaborate heavily in Slack, pair programming, and code reviews. • We work with designers and customer success to understand user problems and build the right thing. • We try to have just enough process to limit the chaos but not so much that it keeps us from getting stuff done. • We value building the right thing well. • We iterate on our product, architecture, and skills to get better at all of them. • We communicate kindly and clearly in a safe environment.

• Design and develop scalable microservices-based applications using Java and Spring Boot • Build and maintain RESTful APIs to enable seamless communication between systems and services • Develop responsive and dynamic user interfaces using React or Angular • Collaborate with cross-functional teams including product, design, and QA to deliver end-to-end features • Participate in system design, architecture discussions, and technical decision-making • Write clean, maintainable, and testable code following best practices and coding standards • Optimize application performance, scalability, and reliability • Work with SQL databases to design schemas, write optimized queries, and manage data efficiently • Contribute to CI/CD pipelines, build automation, and deployment processes • Ensure code quality through unit testing, integration testing, and code reviews • Troubleshoot and resolve production issues, ensuring high availability of applications • Support and implement integrations using middleware platforms such as MuleSoft (good to have)