As a leader within a globally renowned organization, you can make a meaningful impact on employees, customers, and communities around the world. This role presents an unparalleled opportunity for you to take the reins and help shape the future of technology.

 

As a Senior Storage & Data Management Architect at JPMorganChase within Infrastructure Platforms, you manage the architecture for our next generation IaaS distributed storage platform, integrate it into our overall IaaS stack, and serve as a key decision maker for your teams. Apply your deep understanding of infrastructure architecture, applications, processes, and product management to drive results and solve complex issues on projects across teams.

Job responsibilities

Leads infrastructure architecture process implementation to achieve functional objectivesManages multiple complex projects, processes, and initiatives in the functionBe responsible for decisions that influence staffing, budget, and relevant profit and lossMentors and coaches junior architects and technologistsChampions the firm’s culture of diversity, opportunity, inclusion, and respect for team members and prioritizes diverse representation  

 

Required qualifications, capabilities, and skills

Formal training or certification on hardware engineering concepts and 10+ years applied experience with Storage & Data Management.Experience in a modern programming language (C++, Go, Python) and KubernetesSignificant experience with Ceph and other loosely coupled distributed storage architectures.  This must include Production deployment, performance profiling and troubleshooting of large scale enterprise environments.Experience in managing data storage within highly regulated, confidential environments.  Demonstrate a security-first mindset.Experience developing and managing cross-functional teams of infrastructure architects   Experience hiring, developing, and recognizing talent Practical cloud native experience 

 

Preferred qualifications, capabilities, and skills

Experience working at code level, with focus on large scale performance profiling and troubleshooting of a distributed systems, open source stackExperience with Red Hat OpenShift Container Platform and KVMExperience with data engineering / data pipelining