Business Intelligence Engineer II, AMXL Analytics

Amazon Extra Large (AMXL) is looking for a customer focused, analytically and technically skilled Business Intelligence Engineer to drive effective performance measurement and management, innovation and execution in last mile delivery. This position will be responsible for building out analysis and visualization tools and processes to support our growing Amazon Logistics business in Europe.

The successful candidate will be able to effectively retrieve, integrate, visualize and present critical data to improve the efficiency of the package delivery network, and enable efficient management of a large global logistics system. This individual will work with technical and business teams to optimize planning, execution, process improvement and track progress against goals. This role requires an individual with excellent analytical abilities as well as outstanding business acumen and comfort with technical teams and systems. The successful candidate will be a self-starter comfortable with ambiguity, with strong attention to detail, and enjoy working with large scale of data.

Responsibilities

• Maintain and develop data pipeline for EU region
• Automate and improve existing manual processes
• Create tools to help deep diving and investigations into operations execution and business problems
• Analyze and visualize large scale logistics and transaction data to determine user behavior or delivery process problems, and output solid analysis report with recommendation

Qualifications

• 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, correlation analysis

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