As a Business Intelligence Engineer specializing in Cross-Border Business, you will drive data-led decision-making for Amazon’s global expansion initiatives. You will partner with cross-functional teams to define key performance indicators (KPIs), build scalable data pipelines, and deliver actionable insights that optimize cross-border operations, pricing, logistics, and market entry strategies. This role requires deep technical expertise in data engineering, analytics, and visualization, coupled with a nuanced understanding of international market dynamics.

Key Responsibilities:

Define and Track Cross-Border KPIs
Collaborate with product, finance, and operations teams to identify and prioritize KPIs for cross-border business performance. Design dashboards and reports to monitor metrics such as sales growth, fulfillment efficiency, and regional profitability.

Build Scalable Data Pipelines:

Develop and maintain ETL processes to ingest, transform, and analyze cross-border transactional data from diverse sources. Optimize data workflows for Amazon Redshift, Athena, or similar platforms to support real-time analytics.

SQL and Advanced Analytics:

Write complex SQL queries to validate data integrity, automate reporting, and support tests for cross-border initiatives. Apply statistical methods to analyze regional market trends and customer behavior.

Cross-Functional Partnership
Translate ambiguous business questions from global stakeholders into measurable data solutions. Lead investigations into operational anomalies and recommend process improvements.

Data Visualization and Storytelling:

Create interactive dashboards to communicate insights to non-technical audiences. Highlight conversion funnel drop-off points and propose data-driven strategies for improvement.

Basic Qualifications

• 3+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL etc. experience
• Experience with data visualization using Tableau, Quicksight, or similar tools
• Experience with data modeling, warehousing and building ETL pipelines
• Experience in Statistical Analysis packages such as R, SAS and Matlab
• Experience using SQL to pull data from a database or data warehouse and scripting experience (Python) to process data for modeling

Preferred Qualifications

• Experience with AWS solutions such as EC2, DynamoDB, S3, and Redshift
• Experience in data mining, ETL, etc. and using databases in a business environment with large-scale, complex datasets

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