Business Intelligence Engineer, AMZL EU BAT

The goal of Amazon Logistics is to build a world class last mile operation. Amazon aims to exceed the expectations of our customers by ensuring that their orders are delivered as quickly, accurately, and in the most cost effective way as possible. This role is for an passionate, dynamic, analytical, innovative, hands-on, and customer-obsessed business intelligence engineer.

Key job responsibilities
The ideal candidate will have experience working with large datasets and distributed computing technologies. The candidate relishes working with large volumes of data, enjoys the challenge of highly complex technical contexts, and, above all else, is passionate about data and analytics. They are an expert with data modeling, ETL design and business intelligence tools, has hand-on knowledge on columnar databases such as Redshift and other related AWS technologies. They passionately partner with the customers to identify strategic opportunities in the field of data engineering. They are a self-starter, comfortable with ambiguity, able to think big (while paying careful attention to detail) and enjoys working in a fast-paced team that continuously learns and evolves on a day to day basis.

About the team
AMZL EU BAT is a central analytics team within the Supply Chain, Transportation Planning & Operational Excellence (EU STEP) that provides analytics support to all key functions under this organization, but not limited to.- 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- Master's degree, or Advanced technical degree
- Knowledge of data modeling and data pipeline design
- Experience with statistical analysis, co-relation analysis

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