- Experience with data visualization using Tableau, Quicksight, or similar tools
- Experience with one or more industry analytics visualization tools (e.g. Excel, Tableau, QuickSight, MicroStrategy, PowerBI) and statistical methods (e.g. t-test, Chi-squared)
- Experience with scripting language (e.g., Python, Java, or R)
- Master's degree, or Advanced technical degree
- Knowledge of data modeling and data pipeline design
- Experience with statistical analysis, co-relation analysis
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
Amazon strives to exceed the expectations of our customers by ensuring shipments are delivered quickly, safely, and as compliant as possible. Amazon’s Global Risk Audit and Monitoring – Transportation (GRAM-T) Tech builds end-to-end automated software solutions for data-driven risk controls and compliance management.
GRAM-T is looking for a Business Intel Engineer to partner with our customers to build and maintain tools, extract and consolidate data, conduct analysis, and provide insights. The successful candidate will be a customer-obsessed self-starter, comfortable with ambiguity, with strong attention to detail, and with an ability to work in a fast-paced and evolving environment and work effectively with cross-functional and global teams.
Key job responsibilities
- Analyze complex business problems and develop data-driven solutions
- Document business requirements and translate them into functional specifications
- Create and maintain dashboards and reporting systems to track key business metrics
- Support the evaluation and implementation of new tools and processes
- Partner with product, operations, and technical teams to identify process improvements and optimization opportunities
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