Senior Manager, Data Platform Engineering - Kubernetes - Distributed Systems

ServiceNow is an AI control tower for business reinvention, providing an AI platform that brings together data, workflows, and AI. The Senior Manager, Data Platform Engineering will lead a team of engineers building and operating cloud-native platform services, while owning delivery, people management, reliability, scalability, and technical direction.

Responsibilities:

• You will lead, grow, and develop a team of software engineers who design, build, and operate services within the cloud-native platform — owning hiring, onboarding, coaching, performance, and career growth for every member of the team
• You will own end-to-end delivery for your team's domain: setting priorities and roadmap with product and platform leadership, making scope and sequencing trade-offs, and ensuring commitments land predictably from design through production operation
• You will be accountable for the reliability, scalability, and operability of the services your team runs — establishing SLOs, on-call practices, and operational reviews, and driving down incidents and toil across hyperscaler, on-prem, and sovereign environments
• You will partner with principal and distinguished engineers, peer managers, and workload teams to align your team's work with the broader platform architecture, standards, and the needs of the teams that depend on the platform
• You will stay close to the work as a player-coach — reviewing designs and code, weighing in on architectural decisions, and occasionally building — so that technical judgment, not just process, sets the bar for the team
• You will build a healthy, high-trust engineering culture: clear expectations, honest feedback, an inclusive environment, and a team that raises the engineering bar for itself
• You will communicate crisply with leadership and stakeholders about status, risks, and trade-offs, and represent the team in planning, capacity, and escalation conversations

Requirements:

• Experience leveraging or critically thinking about how to integrate AI into engineering and platform work — whether adopting AI-powered tooling across a team, automating operational workflows, building agentic systems for fleet visibility and operations, or reasoning about how AI changes the way a platform team is staffed and run
• 10+ years building production software, including substantial hands-on experience operating distributed systems and running workloads on Kubernetes
• 5+ years managing software engineers, with a track record of hiring, developing, and retaining strong engineers and building teams that deliver
• A track record of leading teams to deliver complex, business-critical systems or services end-to-end, from design through production operation
• Hands-on experience with at least one major hyperscaler (AWS, Azure, GCP), including its core compute, networking, and IAM primitives
• Strong working knowledge of containers and Kubernetes, CI/CD and GitOps-based delivery, and infrastructure-as-code — enough to review designs, challenge assumptions, and make sound technical trade-offs with your team
• Strong communication and stakeholder-management skills, with the ability to explain technical risks and trade-offs to both engineers and senior leadership