New York, NY, US
7 days ago
Sr. Business Intelligence Engineer, Amazon DSP
Amazon Ads operates at the intersection of e-Commerce and Advertising, offering a rich array of digital advertising solutions with the goal of helping our customers find and discover anything they want to buy. Amazon DSP is Amazon’s programmatic advertising product for campaigns spanning Video, Audio and Display across Amazon properties (e.g., Amazon.com, Freevee, Twitch, Fire TV, and Amazon Music) and tens of thousands of third-party websites and apps. We start with the customer and work backwards in everything we do, including advertising. If you’re interested in working to build a unique, world-class advertising offering with a relentless focus on the customer, you’ve come to the right place.

A successful candidate will have a passion for data and analytics, knows and loves working with BI tools, is comfortable accessing and working with big data from multiple sources, and can partner with internal stakeholders to help drive the business. They will have a deep knowledge of business intelligence solutions, possess excellent statistical and analytical abilities, and have the ability to work with technology, product development, and business teams. They will be a self-starter comfortable with ambiguity, with strong attention to detail, an ability to work in a fast-paced and ever-changing environment, and driven by a desire to innovate.

Key job responsibilities
- Partner with Product teams to understand the business requirements and implement solutions to support product plans.
- Design, develop, and maintain scalable, automated, user-friendly systems, reports, and dashboards enabling stakeholders to manage the business and make effective decisions.
- Implement training and documentation solutions that enables stakeholders to get the most out of our self-serve analytics tools.
- Develop and support the analytical technologies that give stakeholders timely, flexible, and structured access to their data.
- Define, develop, and maintain critical business and operational reports reviewed on a weekly, monthly, quarterly, and annual basis.
- Analyze historical data to extract meaningful insights from large and complex data sets to identify trends and support decision making, including written and verbal presentation of results and recommendations.
- Conduct ad hoc data analysis and data quality investigations.
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