Business Intel Engineer II, Amazon Cross-border Analytics and Business Intelligence
Content + Source + Freshness • 14 Dec 2025 • 95% confidence
Offer value
Moderate value arising from the potential to drive significant organizational impact and professional development.
- Role that influences strategic decisions in a large company
- Opportunities for skill development in analytics
- Dynamic work setting requiring adaptability
Pros
- Ability to impact data-driven decision making at a large scale
- Interaction with various teams to enhance business operations
- Growth opportunities in a high-paced work environment
Cons
- High demands and quick turnaround time may lead to stress
- Potentially unclear job roles amid fast-changing responsibilities
- Limited salary insight for the position
Who it's for
Intermediate • Hybrid / office
Good fit
- Intermediate analysts with data experience
- Professional problem solvers keen on collaboration
- Individuals looking to grow in a tech-driven workplace
Not recommended for
- Individuals with minimal experience in analytics
- Those preferring stable roles with predictable tasks
- Candidates who struggle in fast-paced environments
Motivation fit
Key skills
About the job
Description
At Amazon, we're working to be the most customer-centric company on earth. To get there, we need exceptionally talented, bright, and driven people. If you'd like to help us build the place to find and buy anything online, this is your chance to make history. We are looking for a dynamic and organized self-starter to join us as a Senior Business Intelligence Engineer for Amazon Cross-border.
Amazon’s global presence continues to grow quickly – offering millions of products to customers across the world. Our vision is to enable customers from anywhere in the world to purchase any product that we offer globally, through a localized experience at a competitive price and superior delivery experience.
As the Senior Business Intelligence Engineer, you will own our analytical tools, and build new business intelligence solutions end-to-end. You’ll work directly across all teams to provide valuable data-driven insights and recommendations. You will create reporting and analysis that the business will use to measure all aspects of operational performance and cost, and drive both incremental improvement to existing tools and processes and large scale changes in our tools, user interfaces, processes and overall business organization. You will create standard metrics reporting and deliver on ad hoc requests. You will flex across core operational metrics and consumer behavior metrics – linking the two and bringing proactive points of view to leadership, frequently before being prompted. In addition to leading the design, development, and management of our analytical tools and reporting, we will look to this person to provide thought leadership and business analysis support as needed. The successful candidate will demonstrate strong business acumen, experience in developing reporting and analytical infrastructures, strong communication skills, an ability to work effectively with cross functional teams in a fast paced environment and highly ambiguous work space.
Key job responsibilities
In this role, your responsibilities will include:
• Owning the design, development, and maintenance of scalable solutions for ongoing metrics, reports, analyses, dashboards, etc. to support analytical and business needs.
• Development of queries and visualizations for ad-hoc requests and projects, as well as ongoing reporting. Specifically, own all SQL and Tableau – ad hoc, recurring, trouble-shooting.
• Working with team leadership to understand customer needs and concerns as well as define solutions.
• Translating basic business problem statements into analysis requirements. Work with internal customers to define best output based on expressed stakeholder needs.
• Using analytical and statistical rigor to solve complex problems and drive business decisions.
• Designing and driving experiments, A/B testing, outlier deep dives and form actionable recommendations, then managing the implementation of those recommendations.
• Writing queries and output efficiently, and having 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. Converting data to make it analysis-ready.
• Recognizing and adopting best practices in reporting and analysis: data integrity, test design, analysis, validation, and documentation.
• Monitoring and troubleshooting operational or data issues in the data pipelines.
