At Amazon we believe that every day is still day one. We are working to be the most customer-centric company on earth. To get there, we need exceptionally talented, bright, and driven people.
As a Business Intelligence Engineer, you will generate insights that will guide operational excellence and business strategy for our customers. Data analysis is at the core Amazon’s culture, and your work will have a direct impact on decision making and strategy for our organization. You will be gathering customer insights, mining data, making recommendations, and helping senior leaders make key business decisions. The ideal candidates will have excellent analytical abilities, business acumen and judgment, strong technical skills, and superior written and verbal communication skills. They will have a strong bias toward data driven decision making. They will be a self-starter, comfortable with ambiguity, able to think big and be creative (while paying careful attention to detail). Enjoys working in a fast-paced dynamic environment. If you are excited about data, are results oriented, and want to join a growing analytics team within Amazon, this role is for you.

Key job responsibilities
• Supporting strategic project planning, leveraging data to deliver insights, and deep dive on projects.
• Designing, developing and managing tools to support ongoing business reporting. Working with global Business Intelligence counterparts to develop the data pipeline and metric definitions. Building out business dashboards, visualization tools, and finance reports.
• Supporting continuous business performance optimization by designing and driving experiments to form actionable recommendations. Presenting recommendations to business leaders to drive decisions.
• Design, develop and maintain scaled, automated, user-friendly systems, reports, dashboards, etc. that will support the needs of the business.
• Apply deep analytic and business intelligence skills to extract meaningful insights and learning from large and complicated data sets.
• Be hands-on with ETL to build data pipeline to support automated reporting.
• Build various data visualizations to tell the story of business trends, patterns, and outliers through rich visualizations.
• Recognize and adopt best practices in reporting and analysis: data integrity, test design, analysis, validation, and documentation.