Amazon Business Intelligence Engineer WW Ops Finance & L4 

Luxembourg, Luxembourg 

831230166

Key job responsibilities
- Interact with business customers, gather requirements and deliver accurate, easy to use and scalable Business Intelligence solutions such as MAWS (Datanet, Cradle, EC2, etc), NAWS (Glue, Redshift Serverless, S3 etc), Quicksight/Quicksight Q, RStudio Connect Apps and other Amazon proprietary BI tools
- Build ETL, data pipeline jobs, appropriate aggregations, and automated delivery in SQL, Python/R, shell script.
- Design data models on varied database platforms like Redshift, MySQL or object based data stores.
- Recognize and adopt best practices in reporting and analysis: data integrity, test design, analysis, validation, and documentation.
A day in the life
Our team is seeking an experienced Business Intelligence Engineer with excellent data engineering skills along with scripting and analytical abilities. Within this role you will have unique opportunities to work alongside engineers, product managers, data scientists, program managers and finance leaders to help build next gen analytics and data driven reporting supported via one of the largest finance data warehouses and/or datalake. You will be helping scale the supply chain cost allocation/analytics which spans across multiple geographies of North America and Europe with a focus in EU. You will work closely with product managers to design and implement new cost allocation strategies, work with engineers across the transportation network to assess impact of new program rollouts & help build operational and anomaly detection reporting solutions. Amazon has a culture of being builders and you will get to use the latest technology stack offered via AWS and internal amazon tools to help scale big and fast.
Luxembourg, LUX

- Bachelor's degree in engineering, statistics, computer science, mathematics, or a related quantitative field
- 1+ years experience with data visualization using Tableau, Quicksight, or similar tools
- 1+ years experience with data modeling, warehousing and building ETL pipelines
- 1+ years experience writing complex SQL queries
- 1+ years experience using SQL to pull data from a database or data warehouse and scripting experience (Python) to process data for modeling