Role Overview:

Own the data infrastructure that turns Foundry's operational data - scenarios, runs, BOMs, customer usage - into something Post-Sales, Customer Success, and leadership can actually query and trust.

What You'll Do:

- Design and build the data pipeline that moves operational data out of Foundry's tenant-scoped Postgres schemas into an analytics-friendly warehouse, respecting tenant isolation throughout.

- Build the metrics and reporting layer Post-Sales and Customer Success teams use to track customer health, usage, and adoption.

- Own data quality: schema-drift detection, pipeline monitoring, and making sure a broken upstream change doesn't silently corrupt downstream reports.

- Partner with Foundry Core on billing and metering data - usage-based metrics need to be accurate enough to bill against.

- Establish data modeling conventions for a still-young data platform.

What We're Looking For:

- 5+ years of data engineering experience, including building ELT/ETL pipelines from an operational database into a warehouse.

- Strong SQL and experience with a modern data stack (dbt, Airflow, Fivetran, or equivalent - exact tools flexible).

- Experience with multi-tenant data isolation requirements - this pipeline must never leak one customer's data into another's reporting.

- Comfort partnering directly with business stakeholders to define what "the right metric" actually means.

Nice to Have:

- Experience building usage-based billing or metering data pipelines specifically.

- Familiarity with warehouse automation or B2B SaaS customer-success metrics.