Supabase is hiring a remote FinOps Data Engineer!
Supabase is hiring a FinOps Data Engineer to own the data and tooling behind cloud cost management across AWS and GCP. This is a hands-on engineering role, not a pure analyst position: the person will build BigQuery and dbt models that turn raw billing and usage data into reconciled, trustworthy tables, then use those foundations to identify and deliver real savings. The work covers rightsizing, storage lifecycle, data transfer, spot and auto-scaling, cost attribution, chargeback/showback, unit economics, forecasting, statistical anomaly detection, and automated governance using Python, Terraform, and Lambda. The engineer will also partner with Engineering, Finance, and Product, bringing cost considerations into architecture decisions early and explaining savings cases or data-model implications to technical and non-technical audiences. Success requires both technical depth and clear communication, plus comfort with unglamorous, high-leverage work that unblocks other teams. Supabase is a fully remote, globally distributed, open-source-first company, so the role suits someone who can operate asynchronously and work cross-functionally without positional authority.
Key responsibilities
- Analyze AWS and GCP billing, usage, and cost trends to identify and implement savings opportunities such as rightsizing, storage lifecycle policies, data transfer optimization, and spot or auto-scaling.
- Design, build, and maintain BigQuery and dbt models that transform raw billing and usage data into reconciled, trustworthy mart tables for FinOps reporting and analysis.
- Model unit economics and margin by product line and customer segment, extending coverage as new products and segments are introduced.
- Apply statistical forecasting, anomaly detection, and rigorous quantification to cost and usage data, including savings estimates for storage lifecycle and request-cost patterns.
- Build and maintain cost attribution through tagging policies, cost allocation, and chargeback/showback so engineering teams can see and own their spend.
- Automate cost reporting, anomaly detection, alerting, and policy enforcement using Python, Terraform, Lambda, and related tooling.
- Partner with engineering teams on architecture decisions to incorporate cost efficiency early, and work with Finance on forecasting, budget tracking, KPIs, and self-serve dashboards.
Key requirements
- Strong AWS expertise and working GCP knowledge, including pricing models, billing structures, and cost optimization mechanics.
- Data engineering depth with dbt, BigQuery or a comparable modern warehouse, large-scale SQL, and analytics data modeling such as dimensional modeling, incremental models, and testing.
- Data science fundamentals including statistical forecasting, anomaly detection, and experimentation, with judgment about when rigorous modeling is warranted.
- Automation and scripting experience with Python, Terraform or Pulumi, Lambda, or Bash.
- Familiarity with cost and billing tools such as AWS Cost Explorer, Cost and Usage Reports, GCP Billing Reports, and BI or dashboarding tools such as Hex.
- Ability to communicate cost analysis clearly to technical and non-technical audiences, including engineering, finance, and leadership stakeholders.
- Prior experience across data analytics, data engineering, or data science in a FinOps, cloud cost management, or cloud governance context; experience with a dedicated cloud cost management platform is a plus but not required.
- Seniority: Not specified; individual contributor
- Work mode: Remote
- Key skills: AWS, GCP, dbt, BigQuery, SQL, data modeling, Python, Terraform, Lambda, Bash, statistical forecasting, anomaly detection, cost optimization, cost attribution, chargeback/showback
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