Data Engineer

About the role

Mill is a waste prevention technology company reimagining what it means to eliminate waste, starting with food. We build smart systems and infrastructure for homes, businesses, and municipalities that transform food scraps from landfill-bound waste into valuable resources, including chicken feed. Tens of thousands of Mill’s residential food recyclers are already helping households divert millions of pounds of food scraps every year, paving the way for our upcoming launch of Mill Commercial—the industry’s first end-to-end solution for managing, understanding, and preventing food waste in commercial environments (e.g. grocery, restaurants, food services).

Responsibilities

• Design, build, and maintain scalable data pipelines across Mill's product and operational systems
• Build and operate the customer-facing recommendation engine — including LLM-based logic where useful — that turns characterized food waste data into actionable recommendations: purchasing suggestions, anomaly explanations, operational nudges
• Partner closely with product, engineering, data analytics, and marketing teams

Requirements

• 5 years of experience operating data engineering systems in production
• Built and operated data pipelines in production using Python and tools like dbt, Airflow, Fivetran, or similar — including handling failures, backfills, and schema changes after launch
• Strong SQL skills and experience with a cloud data warehouse (e.g., Snowflake, BigQuery, Redshift)
• Experience with recommendation systems or pipelines that combine multiple data sources into a single product-facing output, in production — including recommendation logic built with LLMs
• Set up CI/CD for data pipelines or product logic (automated testing, staged rollout, rollback), and measured whether a change to a recommendation or model actually improved outcomes, not just shipped it
• Bias toward clarity and action
• Comfort working in a collaborative environment where data consumers are partners, not just stakeholders

Qualifications

• Bias toward clarity and action
• Comfort working in a collaborative environment where data consumers are partners, not just stakeholders

Skills

• Exposure to distributed systems concepts (partitioning, consistency, fault tolerance)
• Hands-on experience with infrastructure as code (Terraform, Pulumi) in a cloud environment
• Familiarity with data contract or data mesh patterns
• Experience with event tracking or product analytics

Benefits

The estimated base salary range for this position is $185k to $210k, which does not include the value of benefits or a potential equity grant.

Pay

The estimated base salary range for this position is $185k to $210k, which does not include the value of benefits or a potential equity grant.

Schedule

Not specified