Kindle has changed the way books are published, sold and read across the globe. Independent authors are now able to publish and sell direct to readers through Kindle and print-on-demand offerings, enabling them to reach audiences never before available. Kindle readers are able to download any book in any language in sixty seconds. Come be a part of changing the way the world reads.
Key job responsibilities
Amazon Kindle team is looking for a Data Engineer (DE) to play a significant role in building their large-scale, high-volume, high-performance data integration and delivery services. These data solutions would be primarily used in periodic reporting, and drive business decision making while dealing efficiently with the massive scale of data available through our Data Warehouse as well as our software systems. You will be responsible for designing and implementing solutions using third-party and in-house reporting tools, modelling metadata, building reports and dashboards, and administering the platform software. You are expected to build efficient, flexible, extensible, and scalable data models, ETL designs and data integration services. You are required to support and manage growth of these data solutions.
You must be a self-starter and be able to learn on the go. Excellent written and verbal communication skills are required as you will work very closely with diverse teams.
- Bachelor's degree in statistics, business analytics, data analytics, data science, computer science or related field
- 2+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL etc. experience
- Experience with data visualization using Tableau, Quicksight, or similar tools
- Experience with one or more industry analytics visualization tools (e.g. Excel, Tableau, QuickSight, MicroStrategy, PowerBI) and statistical methods (e.g. t-test, Chi-squared)
- Experience with scripting language (e.g., Python, Java, or R)
- Knowledge of data modeling and data pipeline design
- Experience with statistical analysis, co-relation analysis
- Master's degree in math/statistics/engineering or other equivalent quantitative discipline