Business Intelligence Engineer

- 3+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL etc. experience
- 2+ years of Tableau Desktop, Quicksight or other relevant data visualization software experience
- Bachelor's degree or above in business administration, finance, economics, computer science, data science, engineering, or other related field, or 2+ years of Amazon RME (BB/3P) Full Time Exempt 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
- Experience using SQL (Structured Query Language) to pull data from a database or data warehouse
- Experience using Python scripting to process data for modeling
- Master's degree or above in BI, finance, engineering, statistics, computer science, mathematics or equivalent quantitative field
- Knowledge of Microsoft Excel at an advanced level, including: pivot tables, macros, index/match, vlookup, VBA, data links, etc.
- 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
- Experience developing and presenting recommendations of new metrics allowing better understanding of the performance of the business

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We are looking for a Business Intelligence Engineer to join the Customer Experience (CX) team at Amazon Now. The BIE will own the end-to-end data ecosystem for CX — building scalable ETL pipelines, automated dashboards, and self-service reporting frameworks that track key metrics across the customer journey including conversion funnels, delivery experience, retention, and NPS. The role involves partnering cross-functionally with Product, UX, Engineering, and Operations teams to define success metrics for feature launches, conduct deep-dive analyses on customer behavior and journey pain points, support A/B experimentation, and build anomaly detection to proactively flag CX degradation.