Senior Staff Data Engineer

• Architect and build core data systems and pipelines that power Afresh products, owning reliability and quality from raw data through to production.
• Take on ambiguous, high-leverage data problems and drive them to a shipped solution without waiting for a detailed spec.
• Set technical direction: define architecture, patterns, and abstractions that make customer integrations and product dataflows faster, cleaner, and more repeatable.
• Drive data quality and pipeline reliability, and champion AI-forward engineering to accelerate development.

By building scalable data systems for Afresh's AI platform, you'll directly help grocers reduce food waste—over 200 million pounds prevented last year—contributing to climate change mitigation and a more sustainable food system.

• Extensive experience (typically 8+ years) building data engineering systems at a staff or principal level.
• Deep technical expertise across Python, PySpark, SQL, dbt, Airflow, and modern data platforms (Databricks, Snowflake, or similar).
• Proven ability to own ambiguous, end-to-end problems and set technical direction in a fast-moving environment.
• Strong collaboration and influence skills across engineering, product, and customer-facing teams.

Salary Range in U.S.: $191,000 - $287,000. Comprehensive health & wellness coverage, meaningful equity, 401(k) with company match, flexible workspace with home office stipend and coworking wallets, annual professional development budget, monthly stipends for wellness and telecommunications, and flexible paid time off.

Afresh is an AI platform for grocery that helps partners like Albertsons, Meijer, and Wakefern reduce food waste and maximize sales through proprietary AI. Founded in 2017, it has scaled to 6 enterprise solutions live in over 10% of the U.S. grocery market.