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Business Intelligence Engineer, Amzl Eu Bat

hace 2 semanas


Barcelona, España Amazon EU SARL (Spain Branch) A tiempo completo

Bachelor's degree or higher in a quantitative/technical field (e.g. Computer Science, Statistics, Engineering) - 1+ years of relevant experience in one of the following areas: Data engineering, business intelligence or business analytics - Hands-on experience in writing complex, highly-optimized SQL queries across large datasets - 1+ years of experience in scripting languages like Python, Bash etc - Experience in data modeling, ETL development, and Data warehousing Experience with Oracle, Redshift etc. - Sharp analytical abilities, proven design skills, excellent communication skills - Experience mentoring and training others on complex technical issues

Job summary
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 quickly, accurately, and in the most cost effective way as possible. To get there, we need exceptionally talented, bright, and driven people. If you'd like to help us build a world-class logistics practice, this is your chance to make history.
As a proven senior BI engineer, you will get plenty of opportunities to analyze supply chain, transportation or financial data in a fast-paced environment, in addition to designing algorithms. You will also engage closely with stakeholders and senior business leaders to gather requirements, prioritize projects and define team roadmap. You will conduct deep dive analyses and translate requirements into effective data visualizations and analytical solutions. You’ll also need to mentor the junior analysts while continuing to operate at a strategic level.
- 3+ years of experience as a Business/Financial Analyst or Systems Analyst in a company with large, complex data sources - Experience with AWS services including S3, Redshift, EMR and Apache Spark - Experience with software coding practices is a strong plus - Experience using Linux/UNIX to process large data sets