Amazon Business Analyst Seller Compliance - Data Engineering & Analytics 

Luxembourg, Luxembourg 

892904526

The following technical experience will be of importance in this role, namely the ability to work comfortably using SQL, BI Tools (e.g. Quicksight/Tableau/PowerBI), and scripting languages (e.g. Python). Additionally, experience with designing data schemas for specific reporting use cases will be very valuable in this role.Key job responsibilities
• Organization skills - demonstrated ability to work independently to make complex investigations, have self-discipline and motivation, follow best practices, document work, show diligence and appropriate time management.
• Communication skills - ability to communicate (written and spoken) in the English language. Demonstrated ability to communicate complex technical problems in simple plain stories. Provide useful updates about work accustomed to different audiences.
• Automation of manual data processes, including data quality and validation.
• Ability to effectively transform and aggregate data using optimized querying that appropriately consider scripting best practices and dependencies.
• Reporting, visualization, custom calculations, and security setting in widely available reporting tools, for instance Quicksight or Tableau.
• Ability to translate ambiguous requests and business problems into tangible requirements and solutions.
• Ability to earn trust among widely differing stakeholders of different roles, responsibilities, geographical location, and, culture.

- Bachelor's degree or equivalent
- Experience in a BI role with a technology company or financial institution
- Experience creating complex SQL queries joining multiple datasets, ETL DW concepts
- Experience writing business requirements documents, functional specifications, and use cases
- Experience with reporting and Data Visualization tools such as Quick Sight / Tableau / Power BI or other BI packages
- Experience scripting for automation (e.g., Python, Perl, Ruby)
- Experience in Excel (macros, index, conditional list, arrays, pivots, lookups)

- Experience using very large datasets