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We are looking for a Cloud FinOps Engineer to own and drive cost optimization across our cloud infrastructure and data platforms. This role is for someone who lives and breathes cloud efficiency-who's as comfortable diving into EC2 right-sizing reports as they are tuning Spark jobs, advising Kubernetes cost models, and shaping long-term AWS financial strategy. This is a senior-level, high-ownership role embedded in the Platform team, working across Engineering, Data, and Finance. You'll be responsible for uncovering waste, optimizing cloud spend, and building the tooling, automation, and reporting systems that make FinOps a core discipline-not an afterthought. Our environment is deeply technical and performance-intensive, with significant cost centers in Spark compute, Kubernetes workloads, Snowflake usage, and Java-based microservices. You'll play a critical role in making our systems not just reliable-but cost-effective at scale.
Job Responsibility:
Lead cost optimization efforts across our AWS estate (EC2, EKS, S3, EBS, Lambda, RDS, etc.), delivering measurable savings and performance wins
Analyze and optimize Apache Spark jobs (EMR/EKS) - improve executor tuning, autoscaling, and job scheduling for efficiency
Partner with Data Engineering to optimize Airflow DAGs, reduce pipeline waste, and manage resource-intensive workflows
Reduce Kubernetes costs through node pool optimization, vcluster strategy, pod rightsizing, and non-prod automation
Implement and manage Savings Plans, Reserved Instances, and workload scheduling to maximize discount coverage