> Markdown version of [/jobs/ext/2787814-senior-manager-software-development-ads-performance-measurement](https://www.wearedevelopers.com/jobs/ext/2787814-senior-manager-software-development-ads-performance-measurement). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Manager, Software Development, Ads Performance Measurement - **Company:** Amazon.com, Inc. - **Location:** Seattle, WA, United States - **Experience:** Expert - **Salary:** $242,100.0 - $327,500.0 - **Contract:** Permanent contract - **Skills:** Agile Methodology, Artificial Intelligence, Systems Engineering, Big Data, Distributed Systems, Software Engineering, Systems Architecture, Build Process, Data Pipelines - **Published:** September 8, 2026 - **Apply:** https://dejobs.org/x/x/FB34001F8A24403FA137D6FDCBA3B988/job/ ## About the Role * 10+ years of engineering experience * 5+ years of engineering team management experience * 10+ years of planning, designing, developing and delivering consumer software experience * Experience partnering with product or program management teams * Experience managing multiple concurrent programs, projects and development teams in an Agile environment Preferred Qualifications * Experience partnering with product and program management teams * Experience designing and developing large scale, high-traffic applications ## Description Amazon is continuing to invest in the measurement of its ads products in order to tap into the growing digital advertising marketplace. Amazon Ads' Measurement, AdTech and Data Science (MADS) team is looking for an experienced Senior Manager, Software Development to lead engineering teams building our Performance Measurement systems. You will own engineering teams responsible for how advertisers measure the performance of their ad campaigns, combining deterministic approaches with modeled approaches to deliver a complete and trustworthy view of advertising outcomes across channels, devices, and the full customer journey. This role is at the intersection of big data systems engineering, applied science, and advertiser-facing product delivery. You will lead 30-50 engineers across multiple teams, owning petabyte-scale data pipelines that process billions of events daily, real-time and batch attribution systems, experimentation infrastructure (randomized controlled trials at scale), and privacy-preserving measurement architectures. Your systems directly inform how advertisers allocate billions in ad spend. You think big, have a bias for action, and bring a history of delivering results in complex distributed systems environments. You thrive in ambiguity and are ready to scale advertising measurement. You are equally comfortable diving deep into system architecture as you are setting multi-year technical strategy with senior leadership. The right candidate will possess a strong engineering leadership background, will have demonstrated experience building and operating large-scale data and ads systems, and will have a well-rounded understanding of advertising, causal inference, and privacy-constrained computation. You must be able to thrive and succeed in an entrepreneurial environment, and not be hindered by ambiguity or competing priorities. This means you are not only able to develop and drive high-level technical strategy, but can also roll up your sleeves, dive deep into system designs, and unblock your teams when it matters. You set technical direction, define system architectures, partner deeply with scientists to translate research into production-grade systems, and build engineering organizations that deliver at high velocity. You will work directly with product managers, scientists, and cross-functional teams to define solutions that balance measurement precision with system latency, privacy constraints, and advertiser trust. You drive prioritization, make build-vs-buy decisions, own operational excellence for mission-critical systems, and develop engineering talent across multiple locations. You will also drive AI-native development practices across your organization, leveraging agentic AI tooling to accelerate engineering velocity, automate operational workflows, and fundamentally rethink how measurement systems are built and maintained. 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