Business Intelligence Engineer

- Experience using SQL to pull data from a database or data warehouse and scripting experience (Python) to process data for modeling
- Experience with data visualization using Tableau, Quicksight, or similar tools
- Experience with data modeling, warehousing and building ETL pipelines
- Bachelor's degree in sciences, engineering, finance or equivalent
- Experience with AWS solutions such as EC2, DynamoDB, S3, and Redshift
- Experience in Statistical Analysis packages such as R, SAS and Matlab

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Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

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What is the Amazon Marketplace?

Amazon is the largest marketplace on earth. Millions of customers shop in Amazon’s marketplaces globally. Every day, customers browse, purchase, and review products sold by third-party (3P) sellers right alongside products sold by Amazon. Since 2000, Amazon welcomes companies of all sizes to offer their products, helping them reach hundreds of millions of customers, build their brands, and grow their business.

What is Amazon Strategic Account Services (SAS)?

With increasing complexity of today’s eCommerce and rise of opportunities, the SAS Team aims to leverage the full potential of each Amazon selling partner. Our team provides in-depth strategic consultancy using a data-driven, collaborative, and customer-focused approach to achieve commercial goals of our sellers.

What is the role of a BIE?

As a member of the central product team within SAS, you will assist the business teams in making data-driven decisions by transforming raw information into actionable intelligence through the creation of sophisticated data products.

Key job responsibilities
• Gather and translate business requirements into scalable products that work well within the overall data architecture.
• Develop automated data products including dashboards, reports, self-service tools and data marts.
• Assist the team in supporting and maintaining the data environment.
• Assist the team in supporting the business regarding data management and ad-hoc analysis.