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À propos de ce poste FinOps Data Engineer chez Supabase

Supabase · Télétravail · 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 model beats a rule of thumb.

  • Have automation and scripting skills: Python, Terraform/ pulumi, Lambda, or Bash.

  • Are comfortable with cost/billing tooling: AWS Cost Explorer, Cost & Usage Reports, GCP Billing Reports, and BI/dashboarding (we use Hex).

  • Have experience with, or are comfortable picking up, Linear and Notion as the system of record for tracking and documenting FinOps work.

  • Experience with a dedicated cloud cost management platform (e.g. CloudZero, Vantage, or similar) is a plus, not required.

  • Can analyze cost data and present it clearly to both technical and non-technical audiences.

  • Have prior experience spanning data analytics, data engineering, or data science in a FinOps, cloud cost management, or cloud governance context.

  • Are energized by doing the unglamorous, high-leverage work (the schlep) that unblocks other teams, and by working cross-functionally without positional authority.

What We Offer

  • Fully Remote

    We hire globally. We believe you can do your best work from anywhere. There are no Supabase offices, but we provide a WeWork membership or co-working allowance you can use anywhere in the world.

  • ESOP

    Every team member receives ESOP (equity ownership) in the company. We want everyone to share in the upside of what we’re building together.

  • Tech Allowance

    Use this budget to set up your ideal work environment—laptop, monitor, headphones, or whatever helps you do your best work.

  • Health Benefits

    Supabase covers 100% of health insurance for employees and 80% for dependents, wherever you are. Your wellbeing and your family’s health are important to us.

  • Annual Off-Sites

    Once a year, the entire company gathers in a new city for a week of connection, collaboration, and fun. It’s a highlight of our year.

  • Flexible Work

    We operate asynchronously and trust you to manage your own time. You know what needs to be done and when.

  • Professional Development

    Every team member receives an annual education allowance to spend on learning—courses, books, conferences, or anything that supports your growth.

About the Team

Supabase was born-remote and open-source-first. We believe our globally distributed team is our secret weapon in building tools developers love.

  • ~400 team members

  • 60+ countries

  • 20+ languages spoken

  • Over $1B raised (including our $500M Series F)

  • 540,000+ community members

We move fast, build in public, and use what we ship. If it’s in your project, we probably use it in ours too. We believe deeply in the open-source ecosystem and strive to support—not replace—existing tools and communities.

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