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About the Role:We are looking for a Lead DevOps Engineer (Cloud Engineer) - L4 to drive visibility, efficiency, and savings across our multi-cloud infrastructure. You will lead efforts to measure and reduce CPO (Cost Per Operation), help map infrastructure cost to product usage and revenue, and work closely with engineering teams to optimise their cloud footprints across GCP, AWS and many more.
Responsibilities:
- Cloud Cost Optimization: Design and implement strategies to reduce operational costs across GCP, AWS, Firebase, and managed services like MongoDB Atlas and Elastic.co
- Cost Observability: Build and maintain cost dashboards (using DoiT, GCP BigQuery, AWS Cost Explorer, etc.) to track spend across cloud providers and services at the product, team, and project level
- CPO Analysis: Define and maintain Cost per Operation (CPO) metrics per product/service; collaborate with product owners to align infra cost with revenue generation
- Multi-Cloud Governance: Set up policies, guardrails, budgets, and alerts to prevent cost overruns and enforce efficient resource usage across Kubernetes clusters and cloud services
- Automation & Tooling: Develop automation scripts (using Python, Bash, or Terraform) to detect idle resources, right-size workloads, and enforce tagging strategies
- Billing Analysis: Break down cloud bills by team, sub_team, project, and service using label-based and usage-based filtering; provide actionable insights and recommendations
- Collaboration: Partner with finance, DevOps, platform, and product teams to tie infrastructure cost back to product growth and engineering impact
- Cloud Architecture: Provide guidance on designing cost-efficient cloud-native systems and help teams adopt best practices for storage, compute, and networking usage
Requirements:
- Experience: 5+ years in Cloud Engineering roles with a focus on cost optimization
- Cloud Expertise: Deep hands-on experience with GCP (BigQuery, GKE, Firebase, Pub/Sub), AWS (EC2, S3, Lambda, EKS), and managed services like MongoDB Atlas, Elastic.co, ClickHouse
- Cost Tools: Strong working knowledge of DoiT Cloud Analytics, GCP Billing Export, AWS CUR (Cost & Usage Reports), and BigQuery
- Scripting & Automation: Proficient in Python, Bash, and automation frameworks for cost cleanup and reporting
- Data-Driven: Comfortable querying and visualising cloud billing data to derive unit economics (e.g., cost per user, per API call, per deployment)
- Kubernetes Knowledge: Familiar with cost management in Kubernetes (e.g., node cost allocation, workload optimization, spot/preemptible usage)
- Communication: Ability to translate complex cost insights into actionable plans for engineering and business stakeholders
United States
