Business Intelligence Engineer

- 5+ 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
- Experience in data mining, ETL, etc. and using databases in a business environment with large-scale, complex datasets
- Experience with AWS solutions such as EC2, DynamoDB, S3, and Redshift

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The role of the IES CFX & Prime analytics team is to delight customers with best in class loyalty programs, ordering experience, delivery experience, and post delivery recipient experience.

Joining the Amazon team means partnering with a dynamic and creative group who set a high bar for innovation and success in a fast-paced and changing environment. The BIE is responsible for being able to influence critical business decisions using data and providing insight to product, tech, and category teams to build product interventions to delight customers.

The successful candidate needs to have :
- A passion for numbers, data and challenges.
- High attention to detail and proven ability to manage multiple, competing priorities simultaneously.
- Excellent verbal and written communications skills.
- An ability to work in a fast-paced, complex environment where continuous innovation is desired.
- Bias for action and ownership.
- A history of teamwork and willingness to roll up one’s sleeves to get the job done.
- Ability to work with diverse teams and people across levels in an organization
- Proven analytical and quantitative skills (includes the ability to effectively use tools such as Excel and SQL) and an ability to use hard data and metrics to back up assumptions and justify business decisions.


Key job responsibilities
Key Responsibilities
- Influence business decisions with data.
- Use data resources to accomplished assigned analytical tasks relating to critical business metrics.
- Monitor key metrics and escalate anomalies as needed
- Provide input on suggested business actions based on analytical findings.