Amazon Business Intelligence Engineer GBSA - Global 

Italy, Lombardy, Milan 

422297986

Key job responsibilities
* Partner with internal stakeholders and program managers across multiple teams, gathering requirements and delivering end to end business intelligence solutions.
* Provide timely and actionable insights into current business performance. This will require data gathering and manipulation, synthesis and modeling, problem solving, and communication of insights and recommendations.
* Analyze and visualize process adherence and performance data to articulate user behavior or process problems to support successful execution of the programs.
* Partner with data engineers to identify the source of data and create a data pipeline to collect necessary business inputs to deliver the analytical product.
* Support pilot studies by building robust pilot analyses plan, data collection processes, and analyzing the output to deliver final recommendations.
* Utilize predictive analytics, machine learning and generative BI tools to continuously improve the quality of the analytics products and effectiveness of the business insights
* Develop queries and visualizations for ad-hoc requests and projects, as well as ongoing reporting.A day in the life
You will be working on Redshift, Quicksight, Python to pull, manipulate and present data in dashboards. You will be working with stakeholders to understand analytic business requirements and build dashboards for use in the AMZL network. You will have the opportunity to do basic machine learning models like Clustering, regression required for benchmarking products.

1) 1+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL etc. experience
2) Experience with data visualization using Tableau, Quicksight, or similar tools
3) Experience with one or more industry analytics visualization tools (e.g. Excel, Tableau, QuickSight, MicroStrategy, PowerBI) and statistical methods (e.g. t-test, Chi-squared)
4) Experience with scripting language (e.g., Python, Java, or R)

1) Master's degree, or Advanced technical degree
2) Knowledge of data modeling and data pipeline design
3) Experience with statistical analysis, correlation analysis