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Supabase is hiring a FinOps Data Engineer to drive cost optimization and cloud financial governance across AWS and GCP infrastructure. This is a hands-on engineering role focused on building the data models, pipelines, and analysis that make cost, usage, and margin numbers trustworthy company-wide.
You'll work cross-functionally with Engineering, Finance, and Product teams to identify and ship cloud cost savings, build tooling to maximize efficiency, and cultivate cost awareness across engineering. Key responsibilities include:
- Analyzing billing, usage, and cost trends across AWS and GCP to identify optimization opportunities (rightsizing, storage lifecycle policies, data transfer, spot/auto-scaling), then taking ideas from identification through to realized savings.
- Designing and maintaining BigQuery/dbt models that transform raw billing and usage data (CUR, Storage Lens) into reconciled, trustworthy mart tables.
- Building cost-vs-revenue and customer segmentation models to understand unit economics and margin by product line and customer segment.
- Applying data science techniques (forecasting, anomaly detection, statistical rigor) to cost and usage data.
- Building and maintaining cost attribution systems including tagging policies, cost allocation, and chargeback/showback mechanisms.
- Automating cost governance through reporting, anomaly detection, alerting, and infrastructure-as-code (Python, Terraform, Lambda).
- Partnering with engineering on architecture decisions to embed cost considerations early.
- Supporting Finance on forecasting, reporting, dashboards, and self-serve analytics.
This role emphasizes doing high-leverage, unglamorous work that unblocks other teams and requires strong communication to explain savings cases and data models to technical and non-technical audiences alike.
Requirements:
- Strong AWS expertise and working GCP knowledge, including pricing models, billing structures, and cost optimization mechanics.
- Data engineering depth: dbt, BigQuery (or equivalent modern warehouse), SQL at scale, and data modeling for analytics (dimensional modeling, incremental models, testing).
- Data science fundamentals: statistical forecasting, anomaly detection, experimentation, and judgment on when rigorous models beat rule-of-thumb approaches.
- Automation and scripting skills: Python, Terraform/Pulumi, Lambda, or Bash.
- Comfort with cost/billing tooling: AWS Cost Explorer, Cost & Usage Reports, GCP Billing Reports, and BI/dashboarding (Hex used internally).
- Experience with or willingness to pick up Linear and Notion as systems of record.
- Prior experience in FinOps, cloud cost management, or cloud governance contexts (data analytics, data engineering, or data science roles).
- Ability to analyze cost data and present clearly to both technical and non-technical audiences.
- Preference for experience with dedicated cloud cost management platforms (CloudZero, Vantage, or similar), though not required.
