Amazon Business Intelligence Engineer Amazon Music 

United Kingdom, England, London 

162722212

In this role, you will contribute to the analytics and insights efforts for the marketing attribution project for Amazon Music. You will develop the analytics roadmap and direction for the project, working closely with marketing stakeholders and other Amazon partners to deliver self-service solutions, insights, learning white papers and models to advance our analytics and science offerings. You will also be part of a full stacked team of business intelligence engineers, data engineers, and scientist whom you will be able to collaborate with and learn from. The ideal candidate must be willing to effectively contribute to analytics solutions, prioritize across multiple stakeholders and projects and be ready to jump into a fast-paced, dynamic and fun environment.Key job responsibilities
• Contribute to the analytics and insights efforts for the marketing attribution project for Amazon Music.
• Work as the internal analytics consultant for marketing teams and collaborate on long-term strategy together.
• Define and deliver reporting and visualization that supports the analytical needs of internal business leaders.
• Drive self-service solutions for senior business stakeholders informing marketing investment decisions.
• Use analytical insights to help increase business and team effectiveness against key strategic goals.
• Build a thorough understanding of the streaming music industry, the subscription business model, and key internal partners across Prime, Amazon devices, media and entertainment businesses.
• Partner with analytics and science teams across Amazon entertainment and subscription businesses.
• Educate and evangelize across internal teams on analytics, insights and measurement by writing whitepapers and knowledge documentation and delivering learning sessions.

- 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
- Experience of analyzing and unterpreting data with Redshift, Oracle, NoSQL etc. experience