FinOps Engineer, Cloud & Kubernetes Optimization

In this role, you will help teams understand and optimize the cost of their cloud and containerized workloads. You will analyze usage data, identify opportunities, build lightweight automation, and translate your findings into recommendations that engineering, product, finance, and leadership teams can act on.

You do not need to be an expert in every area of FinOps. We are looking for someone with a strong cloud or engineering foundation who enjoys working with data, solving open-ended problems, and learning new areas.

Why You May Be Interested

• You will have the opportunity to shape how FinOps capabilities are built and delivered, rather than simply operating an established process.
• You will work directly with cloud, Kubernetes, engineering, finance, architecture, and product teams.
• You will see the measurable impact of your work through improved cloud efficiency and cost savings.
• You will have the flexibility to test new ideas, recommend tools, and build practical solutions.
• You will gain exposure to developing areas such as unit economics, AI cost management, and token-based consumption.
• You will join a growing team where initiative, curiosity, and continuous learning are valued.

Job Responsibilities

• Analyze cloud and Kubernetes usage to identify idle capacity, inefficient workloads, cost anomalies, and practical optimization opportunities.
• Partner with engineering and product teams to evaluate recommendations, explain expected impact, and support implementation.
• Build lightweight scripts, API integrations, and repeatable workflows that reduce manual analysis and connect relevant data sources.
• Develop reports, dashboards, forecasts, and cost insights that help teams understand spending trends and plan future cloud usage.
• Support cloud commitment planning, reservations, savings programs, and other strategies that improve overall cloud-cost efficiency.
• Help expand FinOps practices through standards, documentation, education, and tools that enable product and engineering teams to take greater ownership of their cloud costs.

Mandatory Qualifications

• Hands-on experience working with at least one major cloud platform, such as AWS, Microsoft Azure, or Google Cloud Platform.
• Experience analyzing or optimizing cloud infrastructure, containerized applications, or Kubernetes-based workloads.
• Working knowledge of cloud billing, usage, cost allocation, forecasting, or cost-optimization concepts.
• Ability to use Python or another scripting language for basic automation, API calls, data preparation, or systems integration.
• Experience using data to identify trends, investigate issues, and develop clear, actionable recommendations.
• Strong communication skills, including the ability to explain technical and financial information to engineering, finance, product, and leadership audiences.

Preferred Qualifications

• Experience with FinOps, cloud financial management, technology business management, or cloud-cost optimization.
• Familiarity with tools such as Apptio Cloudability, VMware CloudHealth, Finout, Adaptive6, or cloud-native cost-management platforms.
• Experience with Kubernetes cost allocation, workload rightsizing, autoscaling, cluster efficiency, or shared-cost analysis.
• Experience using SQL, Excel, Power BI, Tableau, Datadog, or similar analytical and observability tools.
• Familiarity with Infrastructure as Code, Terraform, CI/CD pipelines, developer portals, or engineering automation workflows.
• Exposure to unit economics, AI cost governance, token consumption, model-selection economics, or FinOps Foundation practices and certifications.