Amazon

Business Intelligence Engineer

2 months agoSeattle, WA

DESCRIPTION

The Retail Pricing team drives the success of Amazon Retail. We build software that makes billions of monthly pricing recommendations on our marketplaces. We earn our customers' trust by consistently delivering the lowest prices possible: we price and publish prices automatically for the millions of products bought worldwide every day by our customers.

As a Business Intelligence Engineer, you will generate insights that will guide operational excellence and product development for our customers. Data analysis is at the core of Amazon's culture, and your work will have a direct impact on decision making and strategy for our team. You will be gathering customer insights, mining data, making recommendations, and helping senior leaders make key business decisions.

This position requires high judgment, excellent analytical abilities, a creative mind; it also offers broad exposure to various business, operational, financial, and technical teams across Amazon.

BASIC QUALIFICATIONS

Bachelor's degree or equivalent experience - 3+ years of experience using SQL - 3+ years as a Business Intelligence Engineer, Business Analyst, Data Engineer, or similar roles

PREFERRED QUALIFICATIONS

• Ability to work in a team environment that promotes collaboration
• Degree in Computer Science, Engineering, Math, Finance, Statistics or a related discipline and 3-5+ years industry experience
Must have three years of experience in the following skill(s):
• Own the design, development, and maintenance of ongoing/new performance metrics, reports, analyses, dashboards, etc. to drive key business decisions
• Familiarity with solutions such as AWS, EC2, S3, or DynamoDB - Knowledge and direct experience using business intelligence reporting tools. (Tableau, QuickSight etc.)
• Build scalable solutions / self-serve platforms that will provide data / KPIs to inform business decision making
• Build various data visualizations to tell the story and let the data speak for itself
• Recognize and adopt best practices in reporting and analysis: data integrity, test design, analysis, validation, and documentation