Amazon Business Intelligence Engineer SMGS Ops - WWSO Sales & Biz 

United States, Washington, Seattle 

114347350

Key job responsibilities
- Work directly with the models/data. Work with large data sets and the technical tools needed to work with them
- Manage complex, manual, revenue routing processes to ensure revenue is reported accurately
- Write high quality SQL queries to retrieve and analyze data from database tables (ex. Redshift, MySQL). Build data models leveraging Python.- Drive towards simple, scalable solutions to difficult problems
- Project-manage multiple workflows and communicate complex analytical results, both written and verbally
- Work with key business stakeholders to understand requirements and shape analytical deliverablesDiverse Experiences
AWS values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.Mentorship & Career Growth
We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.Work/Life Balance
About Sales, Marketing and Global Services (SMGS)

- Bachelor's degree in BI, finance, engineering, statistics, computer science, mathematics, finance or equivalent quantitative field
- 3+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL etc. experience
- Experience with data visualization using Tableau, Quicksight, or similar tools
- Experience using SQL to pull data from a database or data warehouse and scripting experience (Python) to process data for modeling
- Experience with data modeling, warehousing and building ETL pipelines

- 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
- Experience with forecasting and statistical analysis
- Experience with AWS solutions such as EC2, DynamoDB, S3, Redshift, Bedrock, and Lambda
- Strong communication (verbal and written) and interpersonal skills to translate ambiguous business requirements into complex analyses and actionable insights
- Experience with statistical tools, such as R, SAS, or Python.