Business Intelligence Engineer, Listing Analytics

- 3+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL etc. experience
- Experience developing and presenting recommendations of new metrics allowing better understanding of the performance of the business
- Experience in data mining, ETL, etc. and using databases in a business environment with large-scale, complex datasets
- Experience with data visualization using Tableau, Quicksight, or similar tools
- 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 with AWS solutions such as EC2, DynamoDB, S3, and Redshift
- Master's degree in BI, finance, engineering, statistics, computer science, mathematics, finance or equivalent quantitative field

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The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.

USA, WA, Seattle - 99,500.00 - 160,000.00 USD annually
Are you looking for a role that allows you to shape the future of how sellers sell their products globally with Amazon? Do you like working in a start-up like environment with the opportunity to have a significant impact from day 1? Do you have an insatiable curiosity about why Amazon global stores operate as they do and how Amazon could optimize its global selling business? If so, then keep reading as this could be the role for you.
Over 2MM active sellers in 22 countries (and growing) list their products for sale on the Amazon stores. Sellers are a critical part of Amazon’s ecosystem to deliver on our vision of offering the earth’s largest selection and lowest prices.
As a Business Intelligence Engineer (BIE) on Listing Analytics team, you will be responsible for bringing data to the table, specifically seller anecdotes and business metrics. The ideal candidate thrives in working in large and complex data warehouse environments, has excellent verbal and written communication skills, is motivated by developing innovative and simplified solutions to solve complex analytical problems and is passionate about working with large data sets and bringing data together to answer business questions and drive change. These analyses and solutions will be fundamental to finding opportunities and creating new programs aimed at further growing on Amazon stores. In this role you will:

• Engage with leadership and diversified customer groups to understand the needs and recommend business intelligence solutions.
• Partner with engineering teams to define the data elements and data structures that the team should leverage to develop critical seller experience metrics.
• Design, implement, and support platforms that provide business teams ad-hoc access to large datasets for self service deep dives (eg: data visualization tools for non-tech business users)
• Interface with business customers, gather requirements and deliver complete reporting solutions.
• Own the design, development, and maintenance of ongoing metrics, reports, analyses, dashboards, etc. to drive key business decisions.
• Participate in strategic & tactical planning discussions
• Standardize data and report consumption across all customer groups.
• Make recommendations for new metrics, techniques, and strategies to improve the operational and quality metrics.
• Be connected and influential within the Amazon BIE community. Work with data engineering, software development teams to enable the appropriate capture and storage of key data points.