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 the Data Engineering Manager on the Core Data Engineering team, you'll lead the team responsible for integrating customers onto Afresh's platform and continuously improving the processes and code that make those integrations faster and more reliable. Your team will also build core dataflows that power new Afresh products as they launch. This means owning the full lifecycle of customer data integrations: from raw data ingestion through transformation and delivery to downstream product and ML teams, across both new and existing grocery customers. Afresh's customer base is growing fast! We want to integrate customers across all of our products quickly and reliably. You'll drive integration execution, integration velocity, improve data quality and pipeline reliability, and build tooling and processes that make this process seamless. This is a hands-on management role. You'll be deeply involved in technical decisions while also coaching your team, managing execution across multiple customer projects, and collaborating closely with Solutions Engineering, Product, and other engineering teams. What You'll Do - Lead and grow a team of data engineers, providing mentorship, technical guidance, and career development support. - Own execution of customer integrations across multiple product lines (Store Ordering, RecsAPI, DC, Production Planning, and more), ensuring integrations are delivered on time and at a high quality bar. - Build core dataflows that power new Afresh products, working closely with Product and ML teams to understand requirements and deliver reliable data foundations. - Drive integration velocity: improve the speed and predictability of getting new customers from raw data landing to production-ready, leveraging AI tooling, standardized architecture, and strong contractor enablement. - Continuously improve integration processes and shared code: identify patterns across customer integrations and invest in abstractions, templates, and automation that reduce per-customer effort over time. - Collaborate deeply with Solutions Engineers, Product Managers, and customer-facing teams to scope integration work, unblock dependencies, communicate progress, and ensure integrations meet our customers’ needs. - Improve data quality and pipeline reliability by investing in better alerting, self-healing patterns, and resilience to messy or incomplete customer data. - Champion AI-forward engineering practices: evaluate and adopt AI tools and agentic workflows that accelerate development, automate repetitive tasks, and push the team to the bleeding edge of modern data engineering. - Contribute technically: reviewing code and architecture decisions, pairing with engineers on complex problems, and staying close to the work. What Makes You a Great Fit We encourage all highly-qualified candidates to apply, even if they don't meet every listed qualification. - 3+ years of engineering management experience - Strong technical background in data engineering: experience with Python, PySpark, SQL, dbt, Airflow, and modern data platforms (Databricks, Snowflake, or similar). - Track record of shipping high-quality data integrations or ETL systems at scale, and a deep understanding of what makes data pipelines reliable. - Experience managing execution across multiple concurrent projects with different customers or stakeholders, balancing competing priorities with clear communication. - Demonstrated ability to improve team velocity through better tooling, process improvements, or automation. - Genuine enthusiasm for AI-augmented engineering workflows. You've experimented with AI coding tools, agentic workflows, or similar, and have a vision for how they can transform data engineering and uplevel the team. - Comfort working with messy, real-world data from enterprise customers, and the pragmatism to ship solutions that work without over-engineering. - Strong collaboration skills: you're effective working across engineering, product, and customer-facing teams in a fast-paced environment. Nice to Have - Experience in grocery, retail, or supply chain data domains. - Prior experience at a high-growth startup navigating rapid customer expansion. Our Tech Stack - Python, PySpark, dbt - Databricks (Delta Lake, Unity Catalog) - Astronomer (Airflow) for orchestration - Claude, GitHub, Shortcut, Notion for development workflows Why Work Here - We are a mission-driven company that reduces millions of pounds of food waste (and growing!) in grocery stores every year. - Work on challenging, real-world data problems that have a direct and visible impact on customers. - Be part of an engineering culture that's genuinely AI-forward. We want to be on the bleeding edge. - Lead a team at a pivotal inflection point: rapid customer growth means your work directly shapes how Afresh scales. - Collaborative, supportive environment & awesome people :) This position is not eligible for company sponsorship. Salary Range in Canada (CAD): $157,433 - $212,996 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.

• Lead and grow a team of data engineers, providing mentorship, technical guidance, and career development support. • Own execution of customer integrations across multiple product lines (Store Ordering, RecsAPI, DC, Production Planning, and more), ensuring integrations are delivered on time and at a high quality bar. • Build core dataflows that power new Afresh products, working closely with Product and ML teams to understand requirements and deliver reliable data foundations. • Drive integration velocity: improve the speed and predictability of getting new customers from raw data landing to production-ready, leveraging AI tooling, standardized architecture, and strong contractor enablement. • Continuously improve integration processes and shared code: identify patterns across customer integrations and invest in abstractions, templates, and automation that reduce per-customer effort over time. • Collaborate deeply with Solutions Engineers, Product Managers, and customer-facing teams to scope integration work, unblock dependencies, communicate progress, and ensure integrations meet our customers’ needs. • Improve data quality and pipeline reliability by investing in better alerting, self-healing patterns, and resilience to messy or incomplete customer data. • Champion AI-forward engineering practices: evaluate and adopt AI tools and agentic workflows that accelerate development, automate repetitive tasks, and push the team to the bleeding edge of modern data engineering. • Contribute technically: reviewing code and architecture decisions, pairing with engineers on complex problems, and staying close to the work.

• Translate the company's strategic objectives into clear, actionable goals for the team; • Monitor trends and opportunities for continuous improvement, ensuring the team operates aligned with business needs; • Lead complex projects, track success metrics, and remove impediments for the team; • Review and optimize workflows to increase the team's productivity; • Ensure ongoing alignment with Product Managers (PMs), Designers, and other stakeholder teams; • Plan and manage team resource allocation, balancing workload and individual skills.

• manage team priorities and drive alignment • connect customer needs with product vision • recruit, mentor, and grow engineers • ensure execution is predictable and reliable • guide architectural decisions