Manager, Analytics Software Engineering

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

NetApp is seeking a hands‑on, innovative Software Engineering Manager to lead globally distributed software engineering and data science teams responsible for AI‑driven analytics, recommendation systems, intelligent insights, and customer success platforms. This leader will manage teams across multiple locations, building scalable platforms that turn data into actionable intelligence. The role combines strong engineering management with practical expertise in AI, machine learning, and emerging technologies.

The ideal candidate is a hands‑on engineering leader with the technical credibility to guide architecture, solve complex problems, and unblock teams, as well as the organizational leadership to develop people, align distributed teams, and deliver measurable outcomes across a diverse portfolio.

We are looking for someone who is:

• An AI‑first leader who combines technical credibility with the ability to build, coach, and scale distributed engineering and data science teams.
• A practical executor who balances innovation, speed, quality, security, scalability, and operational discipline.
• A business‑focused partner who connects technology investments to measurable customer, product, and organizational impact.
• This player‑coach combines people leadership with technical depth, an AI‑first mindset, and a bias for action. They will guide architecture and critical decisions, stepping in selectively to prototype, troubleshoot, or unblock teams while maintaining accountability through technical leads.

What You’ll Do

Lead by Example

• Serve as a hands‑on technical leader who earns credibility through sound judgment, ownership, and execution.
• Partner with engineers, data scientists, architects, and product leaders to guide architecture, resolve critical issues, and turn ambiguity into action.

Drive an AI‑First Engineering Culture

• Champion responsible AI‑first thinking across products, engineering productivity, and business problem‑solving.
• Help teams apply machine learning, Generative AI, agents, recommendation systems, and predictive models to deliver measurable value.
• Promote responsible, secure, scalable AI adoption while encouraging rapid experimentation and continuous learning.

Lead Global Engineering and Data Science Teams

• Lead and develop software engineering, data science, and technical leadership talent across multiple geographic locations.
• Establish clear decision rights, technical ownership, delivery accountability, and cross‑geo collaboration.
• Build an inclusive, high‑accountability culture and support hiring, career development, performance management, and succession planning.

Deliver Strategic Products and Platforms

• Own execution and operational health across strategic products, shared platforms, and technical workstreams, balancing near‑term delivery with architecture investments.
• Translate priorities into outcome‑based roadmaps with clear milestones, ownership, dependencies, risks, and success measures.
• Ensure visible execution while balancing speed, security, quality, scalability, reliability, and production readiness.

Shape Technical and Product Strategy

• Partner with product, architecture, data, and business leaders to shape strategy and connect engineering investments to measurable outcomes.
• Promote reusable platforms, scalable patterns, pragmatic technology choices, and shared capabilities.

Build Strong Stakeholder Partnerships

• Build strong partnerships with product, program, architecture, analytics, and business leaders.
• Communicate roadmaps, trade‑offs, progress, operational health, risks, and investment needs using measurable outcomes.
• Align distributed teams around shared priorities, architecture, and execution discipline.

Required Qualifications

• Bachelor’s or master’s degree in computer science, engineering, data science, or a related field, or equivalent practical experience.
• 8+ years in software engineering, data platforms, data science, or related disciplines, including 4+ years managing cross‑functional technical teams and leading senior engineers, technical leads, or managers.
• Experience leading globally distributed teams with clear ownership, effective decision‑making, and reliable delivery across time zones.
• Proven delivery of enterprise‑scale, data‑intensive, or AI‑enabled products from concept through production.
• Strong understanding of software architecture, APIs, data pipelines, cloud platforms, and production operations, with the ability to assess trade‑offs across software, data, and AI systems.
• Working knowledge of machine learning, predictive modeling, Generative AI, and the lifecycle for deploying, monitoring, and governing AI‑enabled solutions.
• Ability to translate ambiguous business problems into clear technical approaches and communicate effectively with senior stakeholders.

Preferred Technical Experience

• Experience leading enterprise applications, data platforms, and analytics solutions using modern software, data, and cloud technologies; familiarity with Python, C#, .NET, SQL Server, Azure Data Factory, Azure Databricks, Spark, or Power BI is beneficial.
• Experience with modern data architectures, APIs, microservices, cloud‑native applications, and large‑scale structured and unstructured data.
• Experience building or scaling machine learning, recommendation, predictive analytics, or intelligent decision‑support solutions.
• Familiarity with Azure OpenAI, LLMs, RAG, AI agents, vector databases, MLOps, model monitoring, and responsible AI.
• Knowledge of DevOps, CI/CD, automated testing, observability, and production operations.
• Ability to evaluate emerging technologies and apply them pragmatically to business opportunities.
• Remains technically engaged in architecture reviews, prototypes, design discussions, production troubleshooting, and AI strategy without becoming the teams’ primary implementer.

Compensation

The target salary range for this position is $170,000 - $220,000. 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.

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.