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# Performance Engineer (Cloud Data Plane Engineering)

- **Company:** NetApp, Inc.
- **Location:** San Jose, CA, United States
- **Experience:** Experienced
- **Salary:** $147,900.0 - $220,000.0
- **Contract:** Permanent contract
- **Skills:** Clean Code Principles, Artificial Intelligence, Amazon Elastic Compute Cloud, Cloud Computing, Cloud Storage, Data Structures, Distributed Systems, Perl (Programming Language), Python (Programming Language), Machine Learning, Cloud Services, System Programming, Jupyter, Information Technology, Low Latency
- **Published:** August 3, 2026
- **Apply:** https://www.dice.com/job-detail/c66f6482-86d6-4d0b-93ca-9606fcf808fd

## About the Role

* A minimum of 4years of experience is required.
 * Knowledge of performance analysis, modeling techniques, benchmarking, and workload characterization.
 * Understanding of performance tradeoffs when designing for multi-tenant, elastic cloud environments (latency, throughput, cost, and reliability).
 * Hands-on experience applying AI/ML techniques to performance engineeringUnderstanding of AI/ML workloads and their impact on cloud storage performance.
 * Strong foundations in operating systems, data structures, and standard programming practices; systems programming in C is highly desirable.
 * Proficiency with scripting and automation (Python, shell; Perl acceptable) and comfort working with notebooks (e.g., Jupyter)., * A Bachelor of Science, Master of Science, or PhD Degree in Electrical Engineering or Computer Science; or equivalent experience is required.

## Description

Design, develop, analyze, and optimize cloud software and performance capabilities for cloud storage services and distributed systems. In this role you will collaborate with cross-functional engineering teams to model, measure, analyze, and improve the performance, scalability, and cost-efficiency of cloud platforms?ensuring customer and market requirements are met while balancing quality, cost, and time-to-market. The ideal candidate is systems-focused, analytical and creative, and driven to deliver measurable performance improvements at cloud scale., * Design and execute performance benchmarks/workloads; measure, analyze, interpret, and socialize results to identify improvement opportunities.

 * Apply AI-assisted performance engineering techniques and develop tools (e.g., performance analysis, automated regression triage, and ML-based capacity planning) to accelerate bottleneck analysis and guide optimization priorities.
 * Evaluate design alternatives and prototype performance enhancements across cloud services and distributed components.
 * Collect and analyze customer experience signals and usage patterns; prepare findings and recommendations for engineering and management.


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