The Social Ads team owns Amazon’s automated advertising on Social Media platforms like Facebook, Twitter, Pinterest and Instagram. Our engineering team builds self-optimizing ad personalization engines that leverage integrated Machine Learning, massive data processing and adaptive algorithms to deliver ad performance. We use Social Graph signals and closed loop optimization to power our advertising engine. As a part of our team, you will have a chance to have a ground-up impact on our systems, our business and most importantly, our customers.
Our program goals include driving sales of Amazon products and offers, driving customer acquisition to strategic programs such as Prime Instant Video, Amazon Mom and mobile app downloads. This is relatively new domain and rapidly growing team at Amazon. We're building a top-notch team of engineers, research scientists and engineering leaders. The problems we face are complex and interesting including the information engineering and data mining of Big Data sets from Social Media and Amazon.
We are seeking a top-notch Data Engineer to join our Bangalore team which will own analytics and reporting pipelines in a Big Data processing setup. It will power large scale advertising programs on multiple Social Media ad networks. Successful candidates must be innovative, flexible, have strong leadership skills and be able to work collaboratively with cross-functional business and software development teams to solve critical business problems.
The ideal candidate will have experience working with large datasets, distributed computing technologies and service-oriented architecture. The candidate relishes working with large volumes of data, enjoys the challenge of highly complex technical contexts, and, above all else, is passionate about data and analytics. He/she is an expert with data modeling, ETL design and business intelligence tools, has hand-on knowledge on columnar databases such as Redshift and other related AWS technologies. He/she passionately partners with the customers to identify strategic opportunities in the field of data engineering. He/she is a self-starter, comfortable with ambiguity, able to think big (while paying careful attention to detail) and enjoys working in a fast-paced team.