Data Engineer

JobsCloseBy Editorial Insights

Afresh is seeking a Data Engineer to work remotely from Ontario, building robust ETL pipelines that ingest and transform billions of records with PySpark, Python and dbt to streamline onboarding and empower AI driven data quality. You’ll partner with data, product and ML teams to improve integrations, deploy cutting edge AI tooling for data cleaning and anomaly detection, and optimize ETL performance at scale. The ideal candidate has 2+ years of ETL experience, comfort with messy data, and familiarity with Databricks, Snowflake and dbt, plus strong problem solving and collaboration. To apply, spotlight concrete projects showing end to end pipelines, performance gains, and measurable impact on data quality and onboarding; tailor your resume to the tech stack and demonstrate fast learning and clear communication. Afresh values impact and inclusion.

Afresh is on a mission to eliminate food waste and make fresh food accessible to all. Our first A.I.-powered solution optimizes ordering, forecasting, and store operations for fresh food departments in brick-and-mortar grocers. With our Fresh Operating System, regional and national grocery retailers have placed $1.6 billion in produce orders across the US and we've helped our partners prevent 34 million pounds of food from going to waste. Working at Afresh represents a one-of-a-kind opportunity to have massive social impact at scale by leveraging uncommonly impactful software – we hope you'll 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.

Salary Band in US:

Salary Band in CAN:

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: AR, CA, CO, FL, GA, IL, KY, MA, MI, MT, MO, NV, NJ, NY, NC, OR, PA, TX, WA, WI. However, there may be key roles that will require a candidate/employee to be local to our San Francisco, CA office. In which case this requirement will be included in the job posting details under "Skills and experience" for reference.