Were looking for people who are relentlessly curious and committed to continuous learning. AI is reshaping every function across our business, and we enable every team member, regardless of role or level, to build fluency in AI tools and concepts. Those who thrive here actively seek out new solutions, experiment thoughtfully, and apply what they learn to drive better, faster, smarter outcomes.
As a Senior FinOps Engineer, you will be tasked with being a key architect of our financial sustainability at our company. You won't just track spend, you will build the frameworks that transform complex cloud and usage data into clear, actionable strategies for the business. Joining our global FinOps team, you will act as the bridge between Product Engineering, Finance, and Leadership, ensuring our hyper-growth is matched by world-class unit economics and cloud efficiency.
What will you do?
Primary responsibilities include:
Advanced Analytics & Insights: Architect and maintain sophisticated data models that merge cloud billing data with customer usage metrics to drive deep-dive trend analysis and anomaly detection.
AI & ML Economics: Establish governance and unit-economic tracking for AI-related spend, including GPU utilization, LLM token consumption, and model training costs to ensure high ROI on AI initiatives.
Strategic Allocation: Design and govern complex cost-allocation frameworks (including Kubernetes and shared services) to ensure 100% accountability across product lines and engineering pods.
Cost Tracking & Accountability: Track and maintain critical cloud cost, identify increases and improve cost accountability across org.
Optimization & Commitment Management: Lead the strategy for Reserved Instances, Savings Plans, and CUDs across a multi-cloud environment. Proactively identify architectural rightsizing opportunities.
Forecasting & Capacity Planning: Build predictive models for cloud spend that account for customer acquisition rates, regional expansion, and product roadmap changes to safeguard company margins.
Cost Accountability: Improve cost accountability and mindset across org
Stakeholder Influence: Present quarterly business reviews (QBRs) to senior stakeholders, translating technical cloud complexities into clear financial impact.
Capitalization (CapEx) Reporting: Support the engineering capitalization process by correlating labor effort with project delivery data for financial compliance.
As a Senior FinOps Engineer, you will be tasked with being a key architect of our financial sustainability at our company. You won't just track spend, you will build the frameworks that transform complex cloud and usage data into clear, actionable strategies for the business. Joining our global FinOps team, you will act as the bridge between Product Engineering, Finance, and Leadership, ensuring our hyper-growth is matched by world-class unit economics and cloud efficiency.
What will you do?
Primary responsibilities include:
Advanced Analytics & Insights: Architect and maintain sophisticated data models that merge cloud billing data with customer usage metrics to drive deep-dive trend analysis and anomaly detection.
AI & ML Economics: Establish governance and unit-economic tracking for AI-related spend, including GPU utilization, LLM token consumption, and model training costs to ensure high ROI on AI initiatives.
Strategic Allocation: Design and govern complex cost-allocation frameworks (including Kubernetes and shared services) to ensure 100% accountability across product lines and engineering pods.
Cost Tracking & Accountability: Track and maintain critical cloud cost, identify increases and improve cost accountability across org.
Optimization & Commitment Management: Lead the strategy for Reserved Instances, Savings Plans, and CUDs across a multi-cloud environment. Proactively identify architectural rightsizing opportunities.
Forecasting & Capacity Planning: Build predictive models for cloud spend that account for customer acquisition rates, regional expansion, and product roadmap changes to safeguard company margins.
Cost Accountability: Improve cost accountability and mindset across org
Stakeholder Influence: Present quarterly business reviews (QBRs) to senior stakeholders, translating technical cloud complexities into clear financial impact.
Capitalization (CapEx) Reporting: Support the engineering capitalization process by correlating labor effort with project delivery data for financial compliance.
Requirements:
Ideal candidates will have:
Experience: 4+ years of experience as a dedicated FinOps, Finance, DevOps, or Cloud Infrastructure professional within a large-scale, multi-cloud environment (AWS & GCP preferred).
Data: Expert-level SQL and proficiency in Python for data manipulation. You should be comfortable moving beyond basic reports into data transformation and enrichment.
Visualization: Proven track record of building high-impact BI dashboards (e.g., Tableau, Looker, or Grafana) that tell a story, not just display numbers.
Cloud Architecture: Deep technical understanding of cloud services (Compute, Storage, Networking, and BigQuery/Snowflake) and how their architectural choices impact the bottom line.
Financial Literacy: Solid understanding of accounting principles.
Education: B.Sc. in Computer Science, Industrial Engineering, Data Analytics, or a related field.
Ideal candidates will have:
Experience: 4+ years of experience as a dedicated FinOps, Finance, DevOps, or Cloud Infrastructure professional within a large-scale, multi-cloud environment (AWS & GCP preferred).
Data: Expert-level SQL and proficiency in Python for data manipulation. You should be comfortable moving beyond basic reports into data transformation and enrichment.
Visualization: Proven track record of building high-impact BI dashboards (e.g., Tableau, Looker, or Grafana) that tell a story, not just display numbers.
Cloud Architecture: Deep technical understanding of cloud services (Compute, Storage, Networking, and BigQuery/Snowflake) and how their architectural choices impact the bottom line.
Financial Literacy: Solid understanding of accounting principles.
Education: B.Sc. in Computer Science, Industrial Engineering, Data Analytics, or a related field.
This position is open to all candidates.
