Description

External Fulfillment (EF) operates as team of innovators and creatives who deploy non-standard fulfillment solutions to areas of high opportunity to yield results that benefit our third party partners and Amazon as a whole. The EF team is a rare jewel that owns the end-to-end processes across the whole of Amazon's supply chain (instead of deep siloes). This would allow you to gain insight across the various systems and innovations that sets Amazon apart in the fulfillment space.
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This role will work in an ambiguous environment and build solutions end-to-end (structuring the data, analyzing the data, visualization and/or automation. If you love working with data and solving problems, this is the role for you!

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Key job responsibilities

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- Develop methods and metrics that provide insights to business, operations, and retail teams
- Recognize and adopt best practices in reporting: data integrity, test design, analysis, validation, and documentation
- Write quality code to retrieve and analyze data
- Understand data resources and know how, when, and which to use (and which not to use)
- Continue to move forward in the face of ambiguity and imperfect data. Find a solution around the problem that still maintains a high analytical bar.
- Ensure that decisions are based on the merit of their unbiased data, not the proposer. Stay “true to the data”.
- Clearly communicate results and techniques, both verbally and in writing to peers and business partners.
- Automate reoccurring tasks across Operations and Business teams using SQL/Python.

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Basic Qualifications

- Bachelor's degree or equivalent
- Experience defining requirements and using data and metrics to draw business insights
- Experience creating complex SQL queries joining multiple datasets, ETL DW concepts
- Experience demonstrating problem solving and root cause analysis
- Experience with reporting and Data Visualization tools such as Quick Sight / Tableau / Power BI or other BI packages

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Preferred Qualifications

- Experience scripting for automation (e.g., Python, Perl, Ruby)
- Experience using very large datasets
- Experience in Amazon Redshift and other AWS technologies

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