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Business Intelligence Engineer, Ad Sales Finance Analytics
- New York, New York, United States
- New York, New York, United States
Über
Key job responsibilities
Own the design, development, and maintenance of ongoing metrics, reports, analyses, dashboards, etc. to drive key business decisions.
Own the forecasting model for IX countries and enhance the existing model to align with sales calls while minimizing forecasting errors.
Make recommendations for new metrics, techniques, and strategies to improve team performance and measurement in the future.
Define the data elements and data structure that our team should leverage to enable analytical and reporting capabilities for our business development team.
Design and influence operational best practices for reporting and analytics to enable the team to scale.
Prepare and deliver business reviews to the senior management team regarding progress and roadblocks.
Work with engineering and the data warehouse to enable the appropriate capture and storage of key data points.
Enable effective decision making by retrieving and aggregating data from multiple sources and compiling it into a digestible and actionable format.
Participate in strategic & tactical planning discussions.
A day in the life Your day will be a dynamic blend of data exploration, strategic problem-solving, and cross-functional collaboration. You'll dive deep into complex data landscapes, crafting visualizations and models that reveal hidden patterns and opportunities for Amazon's advertising platforms.
About the team The Ads Sales Finance team is a global group of 30+ Data and BI engineers who partner with finance managers, sales, and product stakeholders to build the forecasting, reporting, and analytics backbone for Amazon Ads. Our mission is to deliver scalable datamarts, models, and dashboards that standardize reporting across regions, minimize forecasting error, and provide leadership with the insights needed to make confident, data-driven decisions. As part of the team, you will collaborate across functions to solve complex problems such as handling massive data volumes, evolving product hierarchies, and aligning multiple upstream and downstream systems—directly impacting how Ads revenue is tracked, forecasted, and managed at scale.
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Sprachkenntnisse
- English
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