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- 2+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL etc. experience
- Experience with data visualization using Tableau, Quicksight, or similar tools
- Experience with one or more industry analytics visualization tools (e.g. Excel, Tableau, QuickSight, MicroStrategy, PowerBI) and statistical methods (e.g. t-test, Chi-squared)
- Experience with scripting language (e.g., Python, Java, or R)
- Experience with SQL
- Experience in the data/BI space
This position will be responsible for building and supporting the business analytics platform that supports the Environmental Assurance and Protection (EAP) team. The incumbent will be responsible for designing and supporting best-in-class data infrastructure and reporting solutions to aid Environmental and Operations team members in decision making. They will continue to raise the bar for the business analytics function and reporting framework.
This role requires an individual with excellent statistical and analytical abilities, deep knowledge of business intelligence solutions and data engineering practices as well as outstanding business acumen and ability to work with various teams across Amazon. The successful candidate will be a self-starter comfortable with ambiguity, with strong attention to detail, an ability to work in a fast-paced and ever-changing environment, and driven by a desire to innovate.
Key job responsibilities
Your responsibilities will include:
You know and love working with business intelligence tools, can model multidimensional datasets, and can partner with customers to answer key business questions. You are analytical and creative, and you don’t quit. You will also have the opportunity to display your skills in the following areas:
- Architect, design, implement, and support a platform providing secured access to large datasets.
- Interface with technical and non-technical customers delivering complete BI solutions.
- Model data and metadata to support ad-hoc and pre-built reporting.
- Own the design, development, and maintenance of ongoing metrics, reports, analyses, dashboards, etc. to drive key business decisions.
- Recognize and adopt best practices in reporting and analysis: data integrity, test design, analysis, validation, and documentation.
- Analyze and solve problems at their root, stepping back to understand the broader context.
- Use data mining, model building, and other analytical techniques to develop and maintain customer segmentation and predictive models to drive the business.
- Respond to high priority requests from senior business leaders.
- Learn and understand a broad range of Amazon’s data resources and know when, how, and which to use and which not to use.
- Continually improve ongoing reporting and analysis processes, automating or simplifying self-service support for secondary datasets
Luxembourg, LUX
- Knowledge of data modeling and data pipeline design
- Experience with statistical analysis, co-relation analysis
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