AWS Cloud Optimization Engineer
Experian · Heredia
Descripcion del puesto
About the role
We are seeking an analytical AWS Cloud Optimization Engineer to manage, evaluate, and optimize AWS usage and costs across multiple applications. The role combines deep AWS knowledge with strong analytical skills to drive cost‑saving initiatives while ensuring performance, scalability, and reliability.
Key responsibilities
- Analyze AWS usage and cost data to identify spend drivers and trends.
- Implement cost‑optimization measures such as rightsizing, scheduling, storage optimization, and removal of unused resources.
- Collaborate with application teams, architects, and engineers to recommend cost‑efficient designs and operational improvements.
- Review infrastructure and cloud designs to ensure effective and responsible use of AWS services.
- Create dashboards, reports, and KPIs that provide visibility into cloud spend, savings, and anomalies.
- Promote FinOps best practices, including governance, tagging standards, forecasting, and ongoing cost accountability.
Required profile
- 4+ years of hands‑on experience with AWS services in a DevOps, cloud engineering, or architecture‑focused role.
- Solid understanding of AWS cost drivers and experience turning usage data into actionable optimization recommendations.
- Familiarity with modern application architectures such as containers, microservices, and cloud‑native deployment patterns.
- Strong communication skills to explain technical and financial concepts to diverse audiences.
Required skills
- AWS (EC2, RDS, S3, EKS, ECS, Lambda, networking, data platforms).
- AWS Cost Explorer, Budgets, and reporting/analytics dashboards.
- DevOps and cloud engineering practices.
- Containers and microservices technologies.
- FinOps principles and cost‑governance.
What we offer
- Medical, life and dental insurance.
- International Share Save Plan.
- Flex work / work from home options.
- Paid time off and annual performance bonus.
- Education reimbursement and family benefits.
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Publicado hace 10 horas
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