The RoleAs a Data Engineer at Mill, you'll touch systems end-to-end - from raw ingestion to the recommendation a customer sees in the app to managing the data warehouse. You'll architect a warehouse model one week and tune recommendation logic the next. You'll partner closely with product, engineering, data analytics, and marketing teams.
What You'll Do- 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
- Design transformation and integration pipelines for food data coming from multiple sources - including agent-based reconciliation where it helps - handling schema changes, validation, and consistency issues
- Partner with data analytics and marketing teams to support self-serve analytics tools
- Own data quality monitoring - build alerting, validation frameworks, and observability tooling
- Bring CI/CD discipline to pipeline - automated tests, staged rollouts, and rollback paths - and track recommendation accuracy over time so we know whether a change actually helped
- Define and maintain the metrics, table endorsements, and business logic that analysts and stakeholders rely on - so everyone across the company is working from the same numbers
What We're Looking For- 5 years of experience operating data engineering systems in production
- Have 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
- Have set up CI/CD for data pipelines or product logic (automated testing, staged rollout, rollback), and have measured whether a change to a recommendation or model actually improved outcomes, not just shipped it
- A bias toward clarity and action
- Comfort working in a collaborative environment where data consumers are partners, not just stakeholders
Nice to Have- Exposure to distributed systems concepts (partitioning, consistency, fault tolerance)
- Hands-on experience with infrastructure as code (Terraform, Pulumi) in a cloud environment
- Experience with Hex, Mixpanel, Tableau, or similar BI/analytics tools
- Familiarity with data contract or data mesh patterns
- Experience with event tracking or product analytics
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. A wide range of factors are considered in making compensation decisions, including but not limited to skill sets, market conditions, experience and training, licensure and certifications, and business and organizational needs.
