Capacity Planning Engineer

At eBay, we're more than a global ecommerce leader — we’re changing the way the world shops and sells. Our platform empowers millions of buyers and sellers in more than 190 markets around the world. We’re committed to pushing boundaries and leaving our mark as we reinvent the future of ecommerce for enthusiasts.

Our customers are our compass, authenticity thrives, bold ideas are welcome, and everyone can bring their unique selves to work — every day. We're in this together, sustaining the future of our customers, our company, and our planet.

Join a team of passionate thinkers, innovators, and dreamers — and help us connect people and build communities to create economic opportunity for all.

About the team and the role:

As a Capacity Planning Engineer at eBay, you will play a vital role in influencing the financial architecture of our ecommerce platform.  You will partner with platform, engineering, search, product, data center, supply chain, and network teams to plan capacity across hybrid environments, including on-premises Kubernetes, Azure, and GCP. This is an outstanding opportunity to lead the charge in optimizing our resource management and ensuring flawless operations across our engineering stack.

The role focuses on forecasting infrastructure demand, improving resource efficiency, and ensuring compute, storage, and network capacity can support traffic growth, new capabilities, and business continuity requirements. You will also contribute to capacity tooling, observability, automation, and analysis across large-scale distributed environments.

What you will accomplish:

• Develop and execute capacity plans across on-premises Kubernetes, Azure, and GCP environments, balancing infrastructure demand with available compute, storage, and network resources.
• Partner with AI, Hadoop, Spark, MapReduce, HDFS, Search, and other platform teams to translate workload characteristics, traffic growth, indexing requirements, and scalability needs into capacity forecasts.
• Analyze utilization, performance, and demand trends to identify bottlenecks and underused resources, and drive improvements in infrastructure efficiency and cost.
• Build dashboards and observability solutions using tools such as Grafana and Prometheus, and provide regular reporting on capacity status, forecasts, trends, and optimization opportunities.
• Conduct scenario and “what-if” modeling to assess the impact of traffic growth, new features, workload changes, and infrastructure updates.
• Support large-scale, federated Kubernetes environments and contribute to tooling and automation for capacity planning, performance analysis, workload optimization, and resource allocation.