Manager, Analytics Software Engineering

Own Every Moment at Net App

At Net App, 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, Net App is where your journey begins. Join teams that innovate to elevate, drive results, and excel together across every function.

Net App 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.

• 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.

• 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 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.

• Own execution and operational health across strategic products, shared platforms, and technical work streams, 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.