Performance Engineer (Cloud Data Plane Engineering)

NetApp; Morrisville (NC); Hybrid; USD 148,000 - 220,000; Full time

Benefits offered by this job

Health Insurance

Life Insurance

Retirement Plans

Paid Time Off

Performance-Based Incentives

Employee Stock Purchase Plan

RSUs

Job summary

NetApp is seeking a systems-focused engineer to design, develop, and optimize cloud storage services and distributed systems. You will collaborate with cross-functional teams to model, measure, and improve performance, scalability, and cost-efficiency of cloud platforms while balancing quality, cost, and time-to-market.

The ideal candidate has strong analytics, hands-on AI/ML application to performance engineering, and solid OS knowledge; C is highly desirable.

Qualifications

• Minimum 4 years of experience in performance engineering or a related field.
• Knowledge of performance analysis, modeling techniques, benchmarking, and workload characterization.
• Understanding of performance tradeoffs in multi-tenant elastic cloud environments (latency, throughput, cost, reliability).
• Hands-on experience applying AI/ML techniques to performance engineering.
• Understanding 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 with notebooks (e.g., Jupyter).

Responsibilities

• 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.

Skills

Performance analysis

AI/ML for performance

C programming

Python

Shell scripting

Jupyter notebooks

System performance modeling

Education

B.Sc. in Electrical Engineering or Computer Science

M.S. in Electrical Engineering or Computer Science

PhD in Electrical Engineering or Computer Science

Tools

Python notebooks

Job description

Own Every Moment at NetApp At NetApp, your ideas power innovation. We lead in intelligent data infrastructure—delivering unified storage, integrated data services, and solutions that help organizations unlock the full potential of their data, from AI to multicloud.

Own Every Moment at NetApp At NetApp, your ideas power innovation. We lead in intelligent data infrastructure—delivering unified storage, integrated data services, and solutions that help organizations unlock the full potential of their data, from AI to multicloud. Ready to innovate and contribute to our path to $10B? Here, you'll collaborate with passionate teams, tackle real-world challenges, and see your impact in how customers transform and grow. If you're ready to bring curiosity, creativity, and drive to every moment, NetApp is where your journey begins. Join teams that innovate to elevate, drive results, and excel together across every function. Job Summary 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.

Responsibilities

• 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.

Job Requirements

• A minimum of 4 years 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).

Education

• A Bachelor of Science, Master of Science, or PhD Degree in Electrical Engineering or Computer Science; or equivalent experience is required.

Compensation: The target salary range for this position is 147,900 - 220,000 USD. The salary offered will be determined by the candidate's location, qualifications, experience, and education and may be outside of this range. Final compensation packages are competitive and in line with industry standards, reflecting a variety of factors, and include a comprehensive benefits package. This may cover Health Insurance, Life Insurance, Retirement or Pension Plans, Paid Time Off, various Leave options, Performance-Based Incentives, employee stock purchase plan, and/or restricted stocks (RSU’s), with all offerings subject to regional variations and governed by local laws, regulations, and company policies. Benefits may vary by country and region, and further details will be provided as part of the recruitment process.

At NetApp, we embrace a hybrid working environment designed to strengthen connection, collaboration, and culture for all employees. This means that most roles will have some level of in-office and/or in-person expectations, which will be shared during the recruitment process.

Equal Opportunity Employer: NetApp is firmly committed to Equal Employment Opportunity (EEO) and to compliance with all federal, state and local laws that prohibit employment discrimination based on age, race, color, gender, sexual orientation, gender identity, national origin, religion, disability or genetic information, pregnancy, protected veteran status, and any other protected classification. Why You'll Thrive at NetApp At NetApp, you won't wait for the perfect moment—you'll make it. The early planning, the extra thought, the bold idea that turns good into great: That's how our people operate and how we continue to push the boundaries of data infrastructure. NetApp is the trusted partner for organizations transforming data into opportunity. As the only enterprise-grade storage service natively embedded in Google Cloud, AWS, and Microsoft Azure, we empower customers to run everything from traditional workloads to enterprise AI with unmatched performance, resilience, and security. Our culture We celebrate mold breakers, bold thinkers, and problem solvers. We reward initiative, impact, and ownership. We provide flexibility so you can balance professional ambition with your personal life. Here, differences are not just welcomed—they drive everything we do. If you're ready to innovate, rise to the challenge, and own every moment - make your next move your best one.

AI Disclosure For select roles, some stages of our hiring process may use artificial intelligence tools to help evaluate applications and candidate selection. These tools support—rather than replace—human decision-making.