Business Intelligence Engineer, Advertiser

Amazon Advertising is one of the fastest-growing businesses at Amazon, helping advertisers of all sizes reach and engage customers across our properties. We are looking for a Business Intelligence Engineer to join the analytics team supporting our Advertiser Experience organization.

Our team is committed to delivering insights on the advertiser experience within the advertising console. We're looking for a teammate who can deep dive into multiple areas of the business, generate dependable Weekly Business Review (W ) reporting, and build dashboards that power regular deep dives and business reviews. Just as important, we need someone who thrives in a fast-changing environment, especially as it relates to AI.

Our team is invested in using AI to accelerate our speed to insight, and we're looking for someone who consistently seeks out opportunities to improve productivity, time to insight, and scalability across the org.

If you're passionate about turning ambiguous business questions into clear, trustworthy analytics, and excited to shape how a team adopts AI to work faster, we'd love to hear from you.

• Build and maintain dependable W  reports and self-service dashboards that leadership and partner teams rely on for regular reviews and deep dives.
• Deep dive into multiple areas of the advertiser experience to surface actionable insights, identify trends, and answer complex business questions.
• Design, develop, and optimize data pipelines, data models, and datasets that are accurate, scalable, and easy to consume.
• Partner with product managers, analysts, and business stakeholders to define metrics, translate requirements into analytical solutions, and drive decisions with data.
• Identify and implement opportunities to apply AI and automation to reduce time to insight and improve team productivity and scale.
• Establish and uphold data quality, documentation, and reporting standards so insights are trustworthy and repeatable.

You might start your day validating the numbers behind this week's W , then jump into a deep dive on a shift in an advertiser experience metric that leadership flagged. In the afternoon, you could be building a new dashboard for an upcoming business review, pairing with an analyst to define a new metric, or prototyping an AI-assisted workflow that cuts a recurring analysis from hours to minutes.

You'll balance recurring reporting commitments with exploratory analysis, always looking for ways to make the team faster and more scalable.

• 3+ years of analyzing and interpreting data with Redshift, Oracle, No
  
  SQL etc. experience
• 1+ years of processing large, multi-dimensional datasets from multiple sources experience
• 1+ years of performing statistical analysis experience
• 1+ years of developing automated reporting experience
• 3+ years of in the job offered or a related occupation experience
• 1+ years of using SQL, ETL (Extract, Transform, Load), or Oracle experience
• Bachelor's degree or foreign equivalent in Computer Science, Engineering, Mathematics, Statistics, Economics, or a related field
• Experience with data visualization using Tableau, Quicksight, or similar tools
• Experience with data modeling, warehousing and building ETL pipelines
• Experience using SQL to pull data from a database or data warehouse and scripting experience (Python) to process data for modeling
• Experience with AWS solutions such as EC2, DynamoDB, S3, and Redshift
• Experience in data mining, ETL, etc. and using databases in a business environment with large-scale, complex datasets

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