Supabase

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:<ul><li>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.</li><li>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.</li><li>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.</li><li>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.</li><li>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.</li><li>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.</li><li>Partner with engineering on architecture decisions: Bring cost into the room early, cost-efficiencies are cheaper to get right at design than to retrofit.</li><li>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.</li></ul>You Might Be a Good Fit If You<ul><li>Have strong AWS expertise and working GCP knowledge, including pricing models, billing structures, and cost optimization mechanics.</li><li>Have data engineering depth: dbt, BigQuery (or an equivalent modern warehouse), SQL at scale, and data modeling for analytics (dimensional modeling, incremental models, testing).</li><li>Have data science fundamentals: statistical forecasting, anomaly detection, and experimentation, and know when a rigorous model beats a rule of thumb.</li><li>Have automation and scripting skills: Python, Terraform/ pulumi, Lambda, or Bash.</li><li>Are comfortable with cost/billing tooling: AWS Cost Explorer, Cost &amp; Usage Reports, GCP Billing Reports, and BI/dashboarding (we use Hex).</li><li>Have experience with, or are comfortable picking up, Linear and Notion as the system of record for tracking and documenting FinOps work.</li><li>Experience with a dedicated cloud cost management platform (e.g. CloudZero, Vantage, or similar) is a plus, not required.</li><li>Can analyze cost data and present it clearly to both technical and non-technical audiences.</li><li>Have prior experience spanning data analytics, data engineering, or data science in a FinOps, cloud cost management, or cloud governance context.</li><li>Are energized by doing the unglamorous, high-leverage work (the schlep) that unblocks other teams, and by working cross-functionally without positional authority.</li></ul><h3>What We Offer</h3><ul><li>Fully RemoteWe 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.</li><li>ESOPEvery team member receives ESOP (equity ownership) in the company. We want everyone to share in the upside of what we’re building together.</li><li>Tech AllowanceUse this budget to set up your ideal work environment—laptop, monitor, headphones, or whatever helps you do your best work.</li><li>Health BenefitsSupabase 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.</li><li>Annual Off-SitesOnce 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.</li><li>Flexible WorkWe operate asynchronously and trust you to manage your own time. You know what needs to be done and when.</li><li>Professional DevelopmentEvery team member receives an annual education allowance to spend on learning—courses, books, conferences, or anything that supports your growth.</li></ul><h3>About the Team</h3>Supabase was born-remote and open-source-first. We believe our globally distributed team is our secret weapon in building tools developers love.<ul><li>~400 team members</li><li>60+ countries</li><li>20+ languages spoken</li><li>Over $1B raised (including our $500M Series F)</li><li>540,000+ community members</li></ul>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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