Manager, Analytics Software Engineering

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.

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.

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