CMT Central Analytics Team owns pricing analytics to drive customer's price perception and competitiveness of Amazon products. We are seeking a creative and goal-oriented Sr. BI Engineer to join our Team to support our data driven decision making.
This role is both strategic and hands-on. It requires an individual with excellent analytical abilities, knowledge of business intelligence solutions, as well as outstanding business acumen and the ability to work with product and teams across CMT. This BIE will support CMT and Retail business teams by owning complex reporting and automating reporting solutions, and ultimately provide insights and drivers for decision making.
The ideal candidate is a motivated self-starter that can work in a fast paced, ambiguous environment with limited supervision. You must be a fast learner who can quickly absorb the nuances of Amazon's varied pricing programs and processes.
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Key job responsibilities
1. Working closely with the multiple CMT business, product/program teams to understand the business drivers, data availability and product challenges. This will require data gathering and manipulation, synthesis and modeling and problem solving.
2. Assist in the development of key product metrics and performance indicators to measure overall performance of the business as well as product contributions to the business.
3. Build self-service reporting platforms, establishing automated processes for large scale data analysis.
4. Understand and write high quality queries to retrieve and analyze data (ongoing reporting and adhoc requests).
5. Manage the data infra-structure for the CMT central analytics team, deciding which data sources to leverage in the process, including influencing teams to assure data is consistent and accurate.
6. Own end-to-end data architecture for new product launches.
Minimum Qualifications
1. 5+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL etc. experience
2. Experience with data visualization using Tableau, Quicksight, or similar tools
3. Experience with data modeling, warehousing and building ETL pipelines
4. Experience in Statistical Analysis packages such as R, SAS and Matlab
5. Experience using SQL to pull data from a database or data warehouse and scripting experience (Python) to process data for modeling
6. Experience with AWS solutions such as EC2, DynamoDB, S3, and Redshift
7. Experience in data mining, ETL, etc. and using databases in a business environment with large-scale, complex datasets
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