Group Product Manager - Containers

Datadog
New York, New York, USAPosted 26 February 2026

Job Description

<p>At Datadog, we're on a mission to build the best platform in the world for engineers to understand and scale their systems, applications, and teams. We operate at massive scale—trillions of data points per day—enabling seamless collaboration and problem-solving across Dev, Ops, and Security teams for tens of thousands of customers worldwide. Our engineering culture values pragmatism, honesty, and simplicity to solve hard problems the right way.</p> <p>The Containers product group sits at the core of Datadog’s Infrastructure business and powers a significant portion of Datadog’s revenue. As modern infrastructure continues to shift toward Kubernetes and containerized workloads, this group is responsible for helping customers operate, secure, and optimize their most critical production environments—reliably and at scale.</p> <p>In this role, you will define the long-term vision and strategy for Datadog’s Containers Live processes products, spanning Kubernetes observability, container runtime visibility, workload health, and the operational workflows that infrastructure teams rely on every day. You will lead a team of product managers building foundational platform capabilities used by thousands of customers running mission-critical workloads in production.</p> <p><em>At Datadog, we place value in our office culture—the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them.</em></p> <p><strong>What You’ll Do: </strong></p> <ul> <li>Lead and grow a team of product managers responsible for Datadog’s Containers and Kubernetes product portfolio.</li> <li>Own the product vision, roadmap, and execution for containers observability, ensuring the products continue to drive meaningful customer value and significant Infra revenue.</li> <li>Define and drive the next generation of Containers products by applying AI and machine learning to help customers understand, operate, and troubleshoot complex containerized systems automatically.</li> <li>Co-define and build the next generation of containers and Kubernetes capabilities as part of the Datadog unified platform, deeply integrated with metrics, logs, traces, security, and CI/CD workflows.</li> <li>Partner closely with engineering leadership to deliver platform-level capabilities that scale across products and customers.</li> <li>Collaborate with other Datadog product teams (APM, Logs, Network, Cloud, Security, Serverless) to improve cross-product workflows and help customers troubleshoot faster and operate with confidence.</li> <li>Work with go-to-market, sales, customer success, and support teams to shape positioning, packaging, and launch strategies for new Containers features.</li> <li>Represent Containers product strategy internally and externally, helping align leadership around priorities and long-term bets.</li> </ul> <p><strong>Who You Are: </strong></p> <ul> <li>Experience: 8+ years of B2B SaaS product management experience, with 2+ years managing and developing a team of product managers.</li> <li>Domain Expertise: Deep familiarity with containers and Kubernetes ecosystems, including how modern infrastructure teams build, deploy, and operate production workloads.</li> <li>Leadership: Proven ability to hire, mentor, and scale high-performing product teams while setting clear direction and expectations.</li> <li>Customer Partnership: Experience working closely with enterprise customers operating complex, large-scale infrastructure.</li> <li>Technical Credibility: Strong technical background that enables effective collaboration with senior engineers and earns trust with highly technical customers.<br>AI Product Fluency: Experience incorporating AI or machine learning into customer-facing products, or strong intuition for where AI can meaningfully improve workflows, decision-making, and automation for infrastructure teams.</li> <li>Data Systems Th ... (truncated, view full listing at source)