Data Engineer

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.
• Helpimproveintegrations 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.

This position is not eligible for employer sponsorship

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