Production Infrastructure & Engineering (PI&E) organization provides the essential platforms and infrastructure hosting solutions that power EA’s live services. Our charter is to make EA’s games and services available to all players anytime and anywhere. To do this, we focus on the high availability of infrastructure, primary services, and studio services. We aim to help developers to experiment and build new games quickly with infrastructure services on-demand and workflows that promote rapid development in the cloud. In all of this, we focus on being there for players where and when they want to play.
- You will support demand across hybrid-Cloud and on-prem. datacenter and 3rd party hosting infrastructure footprint and infrastructure stack
- You will use predictive analytics through modeling data to forecast capacity, identify optimization opportunities, and influence partners.
- You will provide hands-on programming, model development and analytics projects using R, in addition to G-sheets for analysis.
- You will establish an ST and LT capacity plan.
- You will transform current purchasing schedule to planned quarterly fulfillment.
- You will work with GSS, Finance, Studio, and Engineering teams to lead capacity supply signals and ensure needs are met within cost efficiency balance.
- You will recommend cost optimization plans, while prioritizing player experience and systems investment, allocation, and deployment.
- You will identify potential capacity issues and partner with product and service owners to minimize risk and reduce cost-to-serve.
- You will develop a framework to manage the cost and value of multiple features/products/game modes to support Infrastructure’s budget/capacity plan.
- You will provide solution design specifications and technical requirements for developing and improving capacity planning tools and automation.
- You will establish standard demand forecast requirements across titles, services, and partners.
- 3+ years experience with infrastructure capacity planning or engineering
- Bachelor’s Degree in Data Science, Engineering, Statistics, Applied Math, Financial Modeling, or other quantitative fields; Master’s Degree desirable
- Outstanding modeling and analytics skills with strength in R; Python experience desirable
- Experience consolidating complex datasets across multiple unconnected systems to tell a clear story
- Fundamental knowledge of systems infrastructure and how services work with the underlying infrastructure stack
- Experience presenting complex data to both technical and business audiences