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.
Robust 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.

📌 Staff Data Engineer— Platform (Bengaluru)
🏢 GreyOrange
📍 Bengaluru