FinOps Data Engineer

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.

What You'll Be Responsible For

• 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.
• 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 with rigor.
• Build and maintain cost attribution: Tagging policies, cost allocation, and chargeback/showback so engineering teams can see and own their own spend.
• Automate cost governance: Build automated cost reporting, anomaly detection, and alerting. Write scripts and infrastructure-as-code (Python, Terraform, Lambda) enforcing cost policy.
• Partner with engineering on architecture decisions: Bring cost into the room early to ensure cost-efficiencies are built into designs.
• 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.

Qualifications

• Strong AWS expertise and working GCP knowledge, including pricing models, billing structures, and cost optimization mechanics.
• Data engineering depth: dbt, BigQuery (or an equivalent modern warehouse), SQL at scale, and data modeling for analytics (dimensional modeling, incremental models, testing).
• Data science fundamentals: statistical forecasting, anomaly detection, and experimentation.
• 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).
• Familiarity with or ability to learn Linear and Notion as systems of record.
• Experience with dedicated cloud cost management platforms (e.g. CloudZero, Vantage) is a plus.
• Ability to analyze cost data and present it clearly to both technical and non-technical audiences.
• Prior experience across data analytics, data engineering, or data science in a FinOps, cloud cost management, or cloud governance context.