Business Intelligence Engineer, Global

il y a 2 jours

Clichy, France Amazon France Logistique SAS - A41 Temps plein

Experience in analyzing and interpreting data with Redshift, Oracle, NoSQL etc.
- Experience with data visualization using Tableau, Quicksight, or similar tools
- 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)
- Experience with scripting language (e.g., Python, Java, or R)
- Experience with SQL
- Experience in the data/BI space

Key job responsibilities
- Develop analytical solutions to business problems that utilize the highest standards of analytical rigor and data integrity
- Recognize and adopt best practices in reporting and analysis: data integrity, test design, analysis, validation, and documentation
- Write high quality code to retrieve and analyze data
- Analyze and solve business problems at their root, stepping back to understand the broader context
- Design pragmatic analyses and automated metrics that add value to your business area
- Understand data resources
- Seek to understand the business objectives relevant to your area, and align your work to those objectives and seek to deliver business value
- Proactively and continually, improve your level of knowledge about Amazon’s business and relevant data resources

A day in the life
In your role a day could start by working on a new data pipeline on AWS to automate a new process. During the day someone may ask you to perform an urgent deep dive to solve a critical gap in our mechanisms that are affecting our customers. In the time-gaps, there could be space to advance on the document you wanted to present next week.
About the team
Our team works on maximizing our customers experience by creating automated tools that optimize and facilitate the management of our transportation network. We partner with stakeholders from transportation to retail, leveraging statistical and ML model to upgrade our internal technology.
- BS/MS degree, or Advanced technical degree
- Knowledge of data modeling and data pipeline design
- Experience with statistical analysis, co-relation analysis

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