Build the attribution systems that connect ad interactions with real customer outcomes. You'll process more than 50 billion events per day to produce the measurements that power experiences across all of Amazon Ads and help millions of advertisers understand the true value of their campaigns. Attribution is at the heart of advertising measurement, and your work will directly influence how advertising budgets are optimized at global scale. Accurate attribution at Amazon scale is one of the hardest engineering problems in advertising. Our systems connect signals across advertising products, customer journeys, devices, channels and conversion sources. That means solving problems in massive-scale data processing, distributed systems, identity and signal fragmentation, evolving privacy requirements and complex attribution methodologies. The measurements we produce are foundational signals for reporting, campaign optimization, machine learning models, analytics applications and emerging AI-powered advertising experiences. What Makes This Role Stand Out - 50B+ events per day: petabyte-scale data pipelines using Spark, EMR, Apache Iceberg, DynamoDB and other AWS services - Engineering meets science: work directly with applied scientists and economists to turn new measurement methodologies into scalable production systems - End-to-end ownership: take an ambiguous measurement problem through design, implementation, launch and operations - Direct business impact: the data you produce helps millions of advertisers make better investment decisions and powers optimization across Amazon's full advertising suite - Build new, not just maintain: design new architectures that improve scalability, data freshness, correctness, reliability and cost efficiency Key job responsibilities - Design, develop and deliver software that produces measurement data used across Amazon's full advertising suite, including display, search, native and video - Build and maintain petabyte-scale data pipelines and services using Spark, EMR, Apache Iceberg and Java, developing new big data approaches to keep pace with rapid growth - Solve complex attribution challenges as technical requirements, privacy rules and priorities change - Collaborate with applied scientists, economists, product managers and engineers across teams to turn measurement methodologies into scalable production systems - Apply a range of architectural approaches and design patterns to deliver maintainable, scalable, well-tested solutions in a high-throughput environment - Contribute to technical design discussions, identify tradeoffs and propose solutions that balance performance, cost and long-term maintainability - Uphold engineering best practices, including code reviews, testing strategies and operational excellence (alarms, runbooks, monitoring), and mentor peers through design and code reviews About the team The Measurement, AdTech, and Data Science (MADS) team defines and produces the metrics advertisers rely on to analyze the performance of their ad investments. Our charter covers the systems that compute and distribute estimated conversions at massive scale. We work across a rich technology stack, combining AWS services like EMR, Kinesis and AWS Batch with open-source technologies such as Spark and Presto, to deliver fast, reliable measurement at the speed advertisers demand.