Performance Analyst (Benchmark, storage-control-plane, Data Path)

• As a Performance Analysis engineer, you will work as part of a team responsible for modeling, measurement, and analysis of storage systems performance
• The overall focus of the Research and Development function, of which this role is a part, is on competitive market and customer requirements, technology advances, product quality, product cost and time to market
• Performance engineers focus on performance analysis and improvement for new products and features as well as enhancements to existing products and features
• This position requires an individual to be broad-thinking and systems-focused, creative, team-oriented, technologically savvy, and driven to produce results
• Measure and analyze product performance to identify performance improvement opportunities
• Design, implement, execute, analyze, interpret, socialize and apply storage-oriented performance workloads and their results, including the creation of tools and automation as necessary
• Work closely with development teams to drive the performance improvement agenda
• Evaluate design alternatives for enhanced performance and prototype opportunities for performance enhancements
• Create analytical and simulation-based models to predict storage systems performance
• Successfully convey information to stakeholders at many levels related to the position
• Participate as a proactive contributor and subject matter expert on team projects

Job Requirements

• Knowledge of performance analysis and modeling techniques, tools and benchmarking
• Extensive knowledge and experience in computer operating systems, hardware architecture and design, data structures and standard programming practices; systems programming in C is highly desirable
• Strong scripting skills in Perl and Python primarily with Jupyter Notebooks and Shell
• Exceptional presentation and interpersonal skills
• Strong influencing and leadership skills
• The ability to make accurate work estimates and develop predictable plans
• Knowledge of storage and file systems
• Understanding of AL/ML workloads
• Understanding of performance tradeoffs when designing on-prem and cloud systems
• The ability and willingness to adapt to rapidly changing work environments, and enhance automation frameworks (generally python-based) to improve productivity

Education

• 4 to 7 years of experience is preferred
• A Bachelor of Science, Masters of Science, or PhD Degree in Electrical Engineering or Computer Science; or equivalent experience is required