Staff Data Engineer

Summary

Join Afresh, a mission-driven company combating food waste, as a Staff Data Engineer. You will play a key role in scaling and improving customer data integration and processing. This involves designing and implementing ETLs for large datasets, building tools for faster and more accurate customer integrations, and collaborating with cross-functional teams. You will also optimize ETL runtime and data processing scalability, solve data quality challenges, and investigate new technologies. Your work will directly impact customer onboarding and our machine learning grocery solution. Afresh offers a collaborative environment and the opportunity to work on challenging, real-world problems with a direct impact.

Requirements

• 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

Responsibilities

• 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
• 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
• Investigate and implement new technologies into the data platform, focusing on practical solutions that address current pain points and anticipate future needs
• Support team members by mentoring engineers, leading technical discussions, and providing clear, actionable feedback

Benefits

• 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
• Remote work opportunities (specified states)