Staff Data Engineer

Summary

Join Afresh, a company dedicated to eliminating food waste and increasing fresh food accessibility, as a Data Engineer. You will play a key role in shaping how customer data flows through our AI-powered platform, optimizing data ingestion, transformation, and operationalization to reduce food waste for grocery chains. Collaborate with various engineering teams to design and implement robust ETL pipelines, improve customer integrations, and contribute to new features. Your work will directly impact customer onboarding and our machine learning solutions. This position requires experience with data pipelines, PySpark, Python, and SQL, along with a knack for handling messy datasets. You will be working with large-scale data processing and applied AI.

Requirements

• 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
• 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

Responsibilities

• 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

Preferred Qualifications

Experience or strong interest in platforms like Databricks, Snowflake, and dbt

Benefits

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