Amazon

Business Intelligence Engineer II, CMT

Job Description

The CMT Central Analytics Team leads pricing analytics to improve Amazon's competitive position and customer value perception. We seek a Business Intelligence (BI) Engineer to strengthen our data-driven decision-making processes.

This position combines strategic planning with direct implementation. The role requires strong analytical capabilities, experience with BI solutions, business acumen, and the ability to collaborate across CMT teams. The BI Engineer will own and automate reporting solutions, support CMT and Retail business teams, analyze pricing data to identify key decision drivers, and deliver actionable insights.

We need a self-directed professional who thrives in dynamic environments. The successful candidate will demonstrate the ability to work independently, quick comprehension of Amazon's pricing systems, problem-solving skills, and experience managing multiple priorities

Key job responsibilities
1. Partner with CMT business and product teams to analyze business drivers and technical requirements. Develop data models, conduct analysis, and provide solutions to product challenges.

2. Develop and implement key performance indicators (KPIs) to measure business performance and product impact. Transform metrics into actionable insights.

3. Design and build automated, self-service reporting platforms for large-scale data analysis.

4. Write and optimize SQL queries for both scheduled reporting and ad-hoc analysis.

5. Lead data infrastructure management for the CMT central analytics team. Select appropriate data sources and collaborate with teams to ensure data accuracy and consistency.

6. Architect and implement end-to-end data solutions for new product launches, from requirements gathering to deployment- 5+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL etc. experience
- Experience with data visualization using Tableau, Quicksight, or similar tools
- Experience with data modeling, warehousing and building ETL pipelines
- Experience in Statistical Analysis packages such as R, SAS and Matlab
- Experience using SQL to pull data from a database or data warehouse and scripting experience (Python) to process data for modeling


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