Senior Software Engineer, Data

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 As a Senior Data Engineer, you’ll play a key role in scaling and improving how we integrate and process customer data. 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. You’ll also 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 and quickly and power our machine learning grocery solution. What You’ll Do Build tools and frameworks that streamline customer integrations, enabling faster onboarding and better handling of customer data. Create robust ETLs in PySpark and DBT to process billions of records from customer datasets, ensuring data is accurate, reliable, and ready for downstream use. Investigate and implement new technologies into the data platform, focusing on practical solutions that address current pain points and anticipate future needs. 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. Support team members by mentoring engineers, leading technical discussions, and providing clear, actionable feedback. 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. 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. Proven leadership in technical projects, with a willingness to mentor and help others grow. Why Work Here Join a mission-driven company reducing millions of pounds of food waste in grocery stores per year. Work on challenging, real-world problems that have a direct impact on our customers. Be part of a collaborative, supportive team where your ideas are valued and acted on. Use cutting-edge tools and platforms to solve meaningful data challenges. 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 Sal ... (truncated, view full listing at source)