Sr. Business Intelligence Engineer - Amazon Points Program

Job description

描述

At Amazon, we're working to be the most customer-centric company on earth. To get there, we need exceptionally talented, bright, and visionary people. We are looking for a highly analytical Business Intelligence Engineer to join the Amazon Points Program.

As a Sr. 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. You will have the opportunity to work with large and diverse data sets to gather insights and help guide business direction.

The ideal candidate will have excellent analytical abilities, outstanding business acumen and judgment, intense curiosity, 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.

Responsibilities include:
· Owning the design, development, and maintenance of scalable solutions for ongoing metrics, reports, analyses, dashboards, etc. to support analytical and business needs.
· Translate basic business problem statements into analysis requirements.
· Use analytical and statistical rigor to answer business questions and drive business decisions.
· Find and create ways to measure the customer experience to drive business outcomes.
· Develop queries and visualizations for ad-hoc requests and projects, as well as ongoing reporting.
· Write queries and output efficiently, and have in-depth knowledge of the data available in area of expertise. Pull the data needed with standard query syntax; periodically identify more advanced methods of query optimization. Convert data to make it analysis-ready.
· Recognize and adopt best practices in reporting and analysis: data integrity, design, analysis, validation, and documentation.
· Troubleshoot operational data-quality issues.
· Review and audit existing ETL jobs and queries.
· Recommending improvements to backend data sources for increased accuracy and simplicity.