About the job
At Afresh, we are pioneering the integration of AI in the fresh food sector, collaborating with renowned grocery chains such as Albertsons, Wakefern, Meijer, and Stater Bros to facilitate the ordering of billions of dollars worth of fresh produce across more than 12,000 grocery departments nationwide.
After achieving an impressive growth rate of 70% in 2025, we have broadened our platform's capabilities to encompass all fresh departments, introduced our comprehensive store suite, and launched DC Fresh Buying.
Our mission is to reduce food waste and ensure fresh food is accessible for everyone. In 2025, our innovative software contributed to the prevention of 200 million pounds of food waste. If you are searching for a role where your contributions will resonate on a grand scale and drive social good, now is the perfect moment to join us.
About the Role
As a Senior Data Engineer, you will be instrumental in enhancing and scaling our customer data integration and processing capabilities. You will design and implement ETL processes that efficiently handle substantial volumes of customer data, while also developing tools to accelerate and improve the integration experience. Your efforts will directly influence our customer onboarding process and bolster our machine learning grocery solutions.
What You’ll Do
- Develop tools and frameworks that simplify customer integrations, leading to quicker onboarding and improved data handling.
- Create robust ETLs using PySpark and DBT to process billions of records from customer datasets, ensuring accuracy and reliability.
- Explore and implement new technologies within the data platform, focusing on solutions that mitigate current challenges and prepare for future demands.
- Collaborate across product, engineering, and go-to-market teams to design and deliver data solutions for emerging products and features.
- Identify and execute optimizations to enhance ETL runtime and scalability of data processing, streamlining integration efforts.
- Address real-world data quality issues by engaging with messy, incomplete, or inconsistent customer data to derive actionable insights.
- Mentor fellow engineers, lead technical discussions, and provide constructive feedback to support team development.