As a Business Intelligence Engineer (BIE) in the Executive Selling Partner Relations (ESPR) team at Amazon, you will play a crucial role in transforming raw data into actionable insights that drive strategic decision-making. Your primary focus will be on developing and maintaining data pipelines, creating interactive dashboards, and conducting advanced analytics to support the ESPR team's mission of resolving high-stakes escalations from Amazon's selling partners.
This role requires a strong background in data engineering, analytics, and business intelligence, combined with excellent communication skills to effectively translate complex data insights into actionable recommendations for the ESPR team and Amazon leadership.
Key job responsibilities
1. Design, develop, and maintain scalable data pipelines to extract, transform, and load data from various sources within Amazon's ecosystem.
2. Create and optimize SQL queries to retrieve and analyze large datasets related to selling partner issues, escalations, and resolutions.
3. Develop interactive dashboards and reports using tools like QuickSight to visualize key performance indicators (KPIs) and trends.
4. Collaborate with ESPR team members to understand their data needs and translate them into technical requirements.
5. Conduct advanced analytics, including predictive modeling and trend analysis, to identify patterns in selling partner escalations and suggest proactive solutions.
6. Ensure data quality and integrity through rigorous testing and validation processes.
7. Provide data-driven recommendations to improve ESPR processes and reduce escalation rates.
8. Stay current with emerging technologies and best practices in data engineering and business intelligence.- Few 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 using SQL to pull data from a database or data warehouse and scripting experience (Python) to process data for modeling
- 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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