Software Development Manager, Measurement, Ad Tech, and Data Science

Lead the engineering team building the large-scale attribution systems that help advertisers understand how their advertising investments drive meaningful customer and business outcomes — processing more than 50 billion events per day to produce the measurements consumed across all of Amazon Ads. Your team's work directly influences how advertisers understand the value of Amazon Ads, how campaigns and automated systems optimize investments, and ultimately how Amazon's advertising business grows.

Attribution is at the heart of advertising measurement — connecting ad interactions with downstream outcomes such as purchases, subscriptions, and conversions. Building accurate attribution at Amazon scale is a uniquely challenging engineering and scientific problem: our systems must connect signals across complex customer journeys, advertising products, devices, and channels while navigating fragmented identity signals, evolving privacy requirements, changing measurement methodologies, and increasingly sophisticated advertiser needs.

Small decisions in data processing or attribution methodology can affect measurement for millions of advertisers and influence how significant advertising investments are allocated.

This is a hands-on engineering leadership role. You will set technical direction alongside senior engineers, dive deep into architecture and operational issues, challenge designs with concrete alternatives, and build a team capable of solving difficult distributed-systems and data problems. You'll partner closely with product managers, applied scientists, and economists to shape the long-term vision for attribution measurement — determining how Amazon Ads should measure increasingly complex customer journeys, translating new methodologies into scalable production systems, and making deliberate tradeoffs across measurement accuracy, signal coverage, latency, privacy, transparency, and infrastructure cost.

Our technology stack includes large-scale data processing using Apache Spark and Amazon EMR, data storage and processing with Apache Iceberg, DynamoDB, and S3, and distributed services built on AWS cloud-native infrastructure.

• Own the 1-2 year technical vision and strategic direction for a big data measurement platform, defining how attribution evolves to meet increasingly complex advertiser needs and privacy requirements
• Build, manage, and develop a team of world-class engineers — establishing team structure, assessing skills, delegating ownership, and growing future leaders
• Partner with product managers, scientists, and economists to shape the vision for attribution measurement across products, channels, devices, and conversion types
• Set technical direction alongside senior engineers — ensuring high-quality design reviews, driving critical feedback on architecture, and challenging proposals with concrete alternatives
• Deliver robust and scalable solutions toward your vision; invent or incorporate new technologies when needed to stay ahead of growing scale
• Build relationships with peer SDMs, engineers, product managers, and TPMs on partner teams to influence the evolution of ads performance measurement across Amazon Ads
• Oversee resource allocation to balance tactical delivery needs against strategic goals and staff development
• Participate in organizational planning (OP1/OP2) to achieve technical and business objectives; interact with customers, leadership, and your team to construct your plan

The Measurement, Ad Tech, and Data Science (MADS) organization defines and produces the metrics advertisers rely on to analyze the performance of their ad investments. The measurements our systems produce are consumed across Amazon Ads products and increasingly serve as foundational signals for optimization systems, machine learning models, analytics applications, and AI-powered advertising experiences.

• 3+ years of engineering team management experience
• 7+ years of working directly within engineering teams experience
• 3+ years of designing or architecting (design patterns, reliability and scaling) of new and existing systems experience
• Knowledge of…