Work hard. Have fun. Make history.
Amazon strives to be Earth's most customer-centric company where people can find and discover virtually anything they want to buy online. By giving customers more of what they want - low prices, vast selection, and convenience - Amazon continues to grow and evolve as a world-class e-commerce destination.

EU Hardlines Marketing/CX team is seeking a Marketing/CX Business Intelligence Engineer to help accelerate the team’s efforts to improve and automate EU Stores onsite CX feature development.

We seek a quick learner who can familiarize themselves with fast-paced environment, build relationships with cross-functional and cross-category teams and assume ownership for distinct domains on the EU Marketing/CX roadmaps. The right candidate will be flexible, self-starting, action and results-oriented. You must have a high capacity to Learn and Be Curious adapting to the latest changes in the business, systems, tools, and techniques for extracting, processing, analyzing, modeling, and acting on data. The ideal candidate will be a self-starter, highly analytical, consistently think in terms of automation, and intensely detailed with a strong customer focus to drive impact in a fast-paced environment with limited supervision. The ideal candidate shows good judgment in making technical trade-offs between short term and long-term business needs and demonstrate the ability to drive issues to completion.

Key job responsibilities
As a BIE on our team you will focus on exciting and challenging problems. Key responsibilities include:
• Applying your deep analytic and business intelligence skill to extract meaningful insight from large and complicated data sets
• Engaging business stakeholders in constructive dialogues to convert marketing problems into logic problems that can be solved with data, statistics, and/or scripting
• Designing, developing, and implementing scalable, automated infrastructure for data extraction, processing, computation, and delivery
• Designing, developing, and implementing analytical models to underpin Customer facing experiences using statistical methodologies and techniques
• Communicating analytical outputs to stakeholders with a focus on making clear insights, model assumptions, tradeoffs etc.
• Building an expert understanding of technologies and techniques required to build analytical solutions in the Amazon data eco-system. Upskilling in new areas as required for different analytical solutions.