Have you ever seen a smile on someone's face when a package from Amazon arrived only a day after ordering? Have you ever ordered a product on Amazon websites and when the box arrived wondered how you got it so fast? Have you asked yourself how it is possible for Amazon to deliver millions of packages across Europe? Are you passionate about data? Do you want to create the next-generation tools for intuitive data access for transportation operations?
Then we want to hear from you
We are looking for an experienced Business Intelligence analyst to help setup and deliver robust, structured reporting, analytics and models for the all the areas included in the Amazon Transportation Services (ATS) organisation, such Air, Line-haul and Sortation. You will be a key contributor to shaping our strategic streams by equipping the business with tools and insights to drive the different projects and take business decisions. The growth of the business and the increasing complexity of the European transportation network make this role an exciting, interesting, and very challenging proposition.
You will have an eye for detail, are proficient/advanced in SQL/Python and have a knack for solving challenging data and reporting challenges. The role requires you to feel comfortable working with and clearly communicating with other functional teams, regionally and globally.
The position will be based in Luxembourg.
Responsibilities and Duties • You will be reporting to a Program Manager, working intensely with their (larger) project team. • You will be comfortable in a fast-paced, dynamic environment; will be a creative and an analytical problem solver with the opportunity to fulfil the Amazon motto to "Work Hard. Have Fun. Make History". • Creation and ownership of metrics/reporting/dashboards/financial models for the different Business reviews cycles. • Participation in different project streams across ATS, giving visibility to data, metrics, trends to measure performance across the business units; • Work on various analysis and benchmarking exercises to highlight new areas for opportunities, socializing and driving best practice and insights across the operational teams
Basic Qualifications and Experience • Degree in Computer Science, Mathematics, Statistics, or related field; • 3+ year of experience in business intelligence and statistical analysis role; • Experience with SQL and scripting languages such as Python; • Extensive experience with Tableau or other BI tools; • Proficiency in MS Excel; • Experience in building/designing relational databases, reporting/BI platforms or leveraging statistics for data analytics; • Experience in modern data warehousing techniques (dimensional data modelling, ETL workflow development, etc.);
Candidate Profile • Strong team player and the ability to work in a diverse environment with people in various locations; • Excellent verbal and written communication skills; • Impeccable attention to detail, passion for processes, systems and data mining; • Excellent listener, quick learner, and able to handle ambiguity; • Ability to work independently in a fast-paced and rapidly changing environment. • Eager to understand the business and insights behind the numbers; considers him/herself a co-owner of the project/business. Self-starter who can also pro-actively identify challenges/opportunities/solutions;
• Experience with object oriented programming languages (C++, C#, Java, Ruby...); • Prior experience with one of those BI tools: OBIEE, SAP BW, Cognos, Business Objects, Hyperion, BPM, Tableau, Microstrategy; • Data science/Data Management professional with Machine Learning experience; • You have strong interpersonal skills including written and oral communication skill. You are fluent in English; • Strong analytical skills, a passion for metrics and figures, you have very high attention to details and you like to structure and organize things so that they make sense; • Strong bias for action, including the ability to juggle multiple priorities and ability to meet deadlines; • Exposure to AWS is desired but not required.
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