Amazon's display marketing team is seeking a Software Engineer to enable data-driven customer and performance insights for our mobile and web digital advertising programs. Amazon's digital advertising programs, and our Ad Platform, is one of Amazon's fastest growing businesses. We operate on a massive scale (processing over 10B new events per day); and collaborate with teams and services across Amazon to ingest additional customer insight data. Our measurement team is focused on understanding the impact Amazon's digital advertising has on our customers and how we can improve relevance and discoverability of new products. We work with open source technologies such as Hadoop, Hive, Spark, and Presto, as well as AWS services like Elastic Map Reduce, Redshift, Kinesis, and DynamoDB. Be part of a team of industry leading experts that builds and operates one of the largest big data analytics platforms at Amazon. If this sounds interesting, we would love to hear from you!
Amazon's Ad Platform supports both Amazon's own marketing efforts and our third party advertising services. Our platform consists of integrated inventory, ad delivery, and metrics/analytics service (M3), and is one of the largest and most sophisticated ad platforms in the industry. Our team focuses on developing the capabilities to support Amazon's own unique advertising measurement needs and our top strategic programs. Our team develops the mechanisms to ingest new data signals, enable attribution against strategic success events, and automate measurement. In partnership with other analytics and research science teams within Amazon, we develop the systems to automate the calculation of the total value of our advertising and strive to develop the most accurate models for understanding how we influence customers.
We are seeking a strong engineer who can validate our success metrics, shape our strategies, and identify untapped opportunities. To be successful in this role you will need to be innovative in your thinking, effective at cross-team collaboration, experienced in working with data service teams, and have a solid understanding of data flows. You will need to be comfortable working with complex challenges, appreciate white space, and understand the value of rapid test and learn approaches. You will need to be savvy about leveraging large data sets and using a broad range of statistical, data mining, and scripting technologies.