We are looking for a knowledgeable Lead Cloud Engineer with strong AWS expertise to join our team.

As an AWS Cloud Cost Optimization Engineer, you will enhance transparency around cloud expenditures by building a metrics-driven strategy for alerting, reporting, and refining cloud costs. The idóneo candidate brings practical experience in DevOps or SRE, substantial background in analyzing and optimizing costs within large-scale AWS environments, a strong interest in data analysis, and the ability to work well with colleagues throughout the organization.

Responsibilities

Work alongside development and engineering groups to uncover optimization opportunities that boost ROI on cloud resources and enhance cost efficiency
Develop a deep understanding of the client's product, its cloud architecture and deployment approach, and the costs tied to each part of the environment
Guide architects and engineers on resource optimization, minimizing waste, managing capacity, and shaping KPIs
Track cloud expenditures to catch cost spikes and unusual usage patterns, digging into what's driving them




Monitor how cloud reservations and savings plans are being used, coordinating with teams to redirect available capacity
Examine data trends and irregularities to produce insights that guide both strategic and day-to-day decisions
Spot potential savings tied to cloud commitment options (Reserved Instances, Savings Plans, Spot Instances, Committed/Sustained Use) and keep tabs on their usage
Identify inefficient areas and craft practical optimization strategies
Construct, refresh, and sustain dashboards, reports, and automated tools for tracking cost, usage, alerts, and forecasts
Set up dashboards and automated reporting mechanisms to monitor adherence to cost targets
Help establish, refine, automate, and oversee governance for cost optimization policies and best practices
Communicate KPIs and propose savings opportunities to appropriate stakeholders
Coordinate with engineering teams to conf

📌 Lead Cloud Engineer (Argentina)
🏢 EPAM Systems
📍 Argentina