Description
Hewlett Packard Enterprise is seeking a highly skilled Performance Test and Analysis Engineer to drive performance validation, benchmarking, scalability analysis, and optimization across the HPE Alletra Storage MP X10000 Object and File Storage architecture.
As a member of the Storage Performance Engineering team, you will define performance strategies, execute benchmark workloads, analyze system behavior at scale, and drive improvements across the storage software stack. This role requires deep technical expertise spanning computer architecture, operating systems, distributed systems, storage, networking, and software performance engineering.
Responsibilities:
- Design, develop, automate and execute performance validation and benchmark test plans for HPE Alletra Object and File Storage solutions.
- Define performance metrics, KPIs, scalability targets, and release acceptance criteria.
- Analyze performance bottlenecks across compute, memory, storage, networking, operating system, and distributed software layers.
- Participate in root-cause investigations and partner with engineering teams to resolve performance issues.
- Drive workload characterization, capacity planning, and performance tuning initiatives.
- Develop automation, tooling, and analytics solutions using Python and JavaScript.
- Influence product architecture and design through performance insights and data-driven recommendations.
Requirements:
- Bachelor's or Master's degree in Computer Science, Computer Engineering, Electrical Engineering, or related discipline.
- 5+ years of experience in performance engineering, storage systems, distributed systems, or related areas.
- Proven experience diagnosing and resolving complex system performance issues.
Technical Skills:
- Deep knowledge of computer architecture, including CPU, memory hierarchy, NUMA, and I/O subsystems.
- Strong understanding of Linux and operating system internals, including scheduling, memory management, synchronization, and performance profiling.
- Experience with distributed systems, storage architectures, and networking fundamentals.
- Strong programming skills in Python and experience developing automation and performance analysis tools.
- Working knowledge of JavaScript and modern development practices.
- Understanding of parallel programming, concurrency, and scalability concepts.
- Experience with performance benchmarking, profiling, workload modeling, and root-cause analysis.
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