# FinOps Data Engineer  at Supabase

> Find and ship cloud cost savings across AWS and GCP, and build the data pipelines and models that make spend and margin trustworthy.

- Company: Supabase (supabase.com)
- Location: Remote, Global (remote)
- Places: Remote
- Posted: 2026-10-14
- Team: FinOps
- Work mode: Remote
- Apply: https://jobs.ashbyhq.com/supabase/73ddf93b-fe0c-455d-ba27-cdde0d3fb94f
- Page: https://ye.saranatour.dev/jobs/finops-data-engineer-supabase-kn77nspg9gs4fenqq0byrepebn8hbnxq

## The posting

FinOps Data Engineer 
Supabase · Remote, Global

**About the Role**

We're looking for a FinOps Data Engineer to help drive cost optimization and cloud financial governance across our AWS infrastructure and GCP footprint. You'll work cross-functionally with Engineering, Finance, and Product to find and ship savings, build the tooling necessary to maximize efficiency of every dollar spent in the cloud, and cultivate a culture of cost awareness across engineering teams. This role owns the data side of that mission: the models, pipelines, and analysis that make cost, usage, and margin numbers trustworthy across the company.

This is a hands-on engineering role, not an analyst seat. You'll do the schlep work other teams don't have time for, digging into a bucket's access pattern, writing the dbt model or Python pipeline that ships the fix, building the cost-vs-revenue mart that answers a margin question once instead of every time, and chasing a number until it reconciles. Strong communication matters as much as technical depth, you'll regularly explain a savings case or a data model's implications to an engineering team, a finance stakeholder, and a leadership audience in the same week.

**What You'll Be Responsible For**

In this role, you'll:

- **Find and ship savings across AWS and GCP:**Analyze billing, usage, and cost trends to identify opportunities, rightsizing, storage lifecycle policies, data transfer, and spot/auto-scaling. Take ideas from identification through to a realized dollar figure, not just a recommendation.
- **Build and maintain the FinOps data pipeline:**Design and run the BigQuery/dbt models that turn raw billing and usage data (CUR, Storage Lens) into reconciled, trustworthy mart tables, the foundation everything else in FinOps is built on.
- **Build cost-vs-revenue and customer segmentation models:**Model unit economics and margin by product line and customer segment, and extend coverage as new products and segments come online.
- **Apply data science to cost and usage data:**Build forecasting models, detect anomalies statistically rather than by threshold alone, and quantify savings opportunities (e.g. storage lifecycle, request-cost patterns) with rigor a spreadsheet can't match.
- **Build and maintain cost attribution:**Tagging policies, cost allocation, and chargeback/showback so engineering teams can see and own their own spend. This is foundational work other savings work depends on.
- **Automate cost governance:**Build automated cost reporting, anomaly detection, and alerting. Write the scripts and infrastructure-as-code (Python, Terraform, Lambda) that enforce cost policy rather than relying on manual review.
- **Partner with engineering on architecture decisions:**Bring cost into the room early, cost-efficiencies are cheaper to get right at design than to retrofit.
- **Work with Finance on forecasting and reporting:**Support budget tracking and financial KPIs; build dashboards and self-serve analytics engineering and finance can both read.

**You Might Be a Good Fit If You**

- Have strong AWS expertise and working GCP knowledge, including pricing models, billing structures, and cost optimization mechanics.
- Have data engineering depth: dbt, BigQuery (or an equivalent modern warehouse), SQL at scale, and data modeling for analytics (dimensional modeling, incremental models, testing).
- Have data science fundamentals: statistical forecasting, anomaly detection, and experimentation, and know when a rigorous