Sr Business Intel Engineer (BIE), EU Concessions

- Experience programming to extract, transform and clean large (multi-TB) data sets
- Experience with theory and practice of design of experiments and statistical analysis of results
- Experience with AWS technologies
- Experience in scripting for automation (e.g. Python) and advanced SQL skills.
- Experience with theory and practice of information retrieval, data science, machine learning and data mining
- Experience working directly with business stakeholders to translate between data and business needs
- Experience with SQL
- Experience with data visualization using Tableau, Quicksight, or similar tools
- Experience in the data/BI space
- Experience managing, analyzing and communicating results to senior leadership

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We are open to hire you in London, Munich, Luxembourg, Madrid and Milan locations.

We are looking for a talented Business Intelligence Engineer, dedicated and customer-obsessed professional to drive the development of one of the most strategic projects for EU Retail: the high-ASP market segment.

Our vision is to make Amazon the most trusted and preferred destination for Consumer Electronics & Entertainment (TCEE) for both consumers and businesses. Key to achieving this will be addressing the underserved high-ASP market segment.

In this role, you will develop your analytical skills and will learn to work with various stakeholders while driving challenging changes. Focusing on customer experience as the ultimate end-goal, you will push your analytical skills to the highest standards. As you become embedded in the day-to-day team operations, you will learn hands-on what the key drivers are for success in the e-commerce business.


Key job responsibilities
Key job responsibilities
• Design, develop and maintain scaled, automated, user-friendly systems, reports, and dashboards enabling stakeholders to manage the business and make effective decisions.
• Work with PMs and Business stakeholders in understanding the business requirements and implementing solutions to support analytics and reports.
• Conduct ad hoc data analysis and data quality investigations.
• Implement training and documentation solutions that enables stakeholders to get the most out of our self-serve reporting tools.
• Defining, developing and maintaining critical business and operational reports reviewed on a weekly, monthly, quarterly, and annual basis
• Analysis of historical data to extract meaningful insights and learnings from large and complicated data sets identify trends and support decision making, including written and verbal presentation of results and recommendations
• Collaborating with software development teams to implement analytics systems and data structures to support large-scale data analysis and delivery of machine learning models