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). At Mill, we are passionate about building easy-to-use, beautifully designed technologies that keep food in the food system and out of landfills.
As a Data Engineer at Mill, you'll build and maintain the core data infrastructure that powers analytics and product data across the company — ingestion pipelines, warehouse modeling, data quality, and the self-serve analytics platform (Hex + Snowflake) our business teams rely on. You'll work closely with the Senior Data Engineer owning our recommendations platform, contributing to and supporting that work as needed, with the opportunity to grow into deeper recommendation/LLM-based work over time. 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
- Manage and maintain data infrastructure that powers our product and operational systems, ensuring it's reliable and ready to feed external customers and downstream analytics
- Collaborate with software engineers to instrument new product features and ensure event data flows cleanly
- Help build and maintain the self-serve analytics platform in Hex and Snowflake for internal business teams
- Help maintain the metrics, table endorsements, and business logic that analysts and stakeholders rely on
- Own data quality monitoring — build alerting, validation frameworks, and observability tooling so data issues get caught before they become business problems
- 3-5 years of experience operating data engineering systems in production
- Have built and operated data pipelines in production using Python, SQL, and tools like dbt, Airflow, Fivetran, or similar against a cloud data warehouse (e.g., Snowflake)
- Have used Infrastructure as Code (e.g., Terraform, Pulumi) to provision and manage data infrastructure, with CI/CD discipline for pipeline and infra changes (automated testing, staged rollout, rollback)
- Experience working with transactional databases (e.g., PostgreSQL, Amazon RDS) as a data source, including understanding how OLTP systems differ from warehouse/analytical workloads
- Comfort working in a collaborative environment where data consumers are partners, not just stakeholders, and comfort moving between different types of work as priorities shift
- A bias toward action
- Exposure to recommendation, personalization, or LLM-based product logic — not required, but a strong plus given the team's direction
- Experience building or supporting self-serve analytics tooling (Hex, Looker, or similar)
- Exposure to distributed systems concepts (partitioning, consistency, fault tolerance)
- Experience with Mixpanel, Tableau, or similar BI/analytics tools
- Familiarity with data contract or data mesh patterns, or RBAC/access governance on a warehouse
- 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.
Skills Required
- 3-5 years of experience operating data engineering systems in production
- Production experience building and operating data pipelines using Python and SQL
- Experience with dbt, Airflow, Fivetran, or similar data pipeline tools
- Experience working with a cloud data warehouse such as Snowflake
- Experience using Infrastructure as Code tools such as Terraform or Pulumi
- Experience with CI/CD practices for pipeline and infrastructure changes, including automated testing, staged rollout, and rollback
- Experience with transactional databases such as PostgreSQL or Amazon RDS as data sources
- Understanding of differences between OLTP systems and warehouse or analytical workloads
- Collaborative approach and ability to work directly with data consumers
- Exposure to recommendation, personalization, or LLM-based product logic
- Experience building or supporting self-serve analytics tooling such as Hex or Looker
- Exposure to distributed systems concepts including partitioning, consistency, and fault tolerance
- Experience with Mixpanel, Tableau, or similar BI and analytics tools
- Familiarity with data contracts, data mesh patterns, or warehouse RBAC and access governance
- Experience with event tracking or product analytics
Mill Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Mill and has not been reviewed or approved by Mill.
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Fair & Transparent Compensation — Pay is positioned as competitive for several senior technical and business roles, supported by multiple six‑figure base ranges in recent postings. Total compensation snapshots commonly cluster in the mid‑ to high‑$100Ks for individual‑contributor roles, reinforcing a generally market-competitive posture for the Bay Area.
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Leave & Time Off Breadth — Time-off coverage appears broad, including paid holidays, paid sick days, flexible time off, and an unlimited vacation policy, with some company-wide time off. The overall setup signals strong flexibility for managing personal time, though day-to-day use may depend on team norms.
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Healthcare Strength — Core health coverage is described as comprehensive, including medical, dental, and vision, alongside wellness programs and an FSA. The package breadth suggests a solid baseline consistent with tech-startup standards.
Mill Insights
What We Do
We’re on a mission to eliminate waste for good, starting with the food that ends up in landfills. Did you know that more than half of the food in landfills comes from home kitchens (ReFED)? And food in landfills turns into methane – which is 80x more potent than CO2 over a 20-year period (IPCC). At Mill, we’re working to turn kitchen scraps into food for chickens. This keeps food in our food system and out of landfills.
Why Work With Us
Food isn't trash. Mill keeps it from stinking up your kitchen – and the planet.
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