Business Intelligence Engineer 1
Amazon
Business Intelligence Engineer 1
Amazon
Sells products online and rents cloud computing
The Global Reporting & Standards (GRS) team within the Global Reliability and Maintenance Engineering (RME) Central Team is looking for an exceptional business intelligence engineer to join us. In this role, you will work on an analytical team to bust myths, create insights, and produce recommendations to help Central RME to deliver world class service to the Amazon network. As part of the team will be involved in all phases of research, experiment, design and analysis, including defining research questions, designing experiments, identifying data requirements, and communicating insights and recommendations. You'll also be expected to continuously learn new systems, tools, and industry best practices to analyze big data and enhance our analytics. These are exciting fast-paced businesses in which we get to work on extremely interesting analytical problems, in an environment where you get to learn from other engineers and apply business intelligence to help leadership make informed decisions.
Key job responsibilities
You build mid-size to large BI solutions or components of larger solutions. Your focus is at the team level, working on a major portion of existing or new BI artifacts (e.g., contributing to the team’s datamart) or owning a difficult report or analysis.
You assume responsibility for the code, queries, reports and analyses you inherit or produce. You get your analyses and code reviewed. You test your code by validating outputs against source data, business logic, and related metrics
You have a deep understanding of data lineage of your team’s BI solutions: the technical systems by which the data is generated; how the metrics are aggregated; and how the resulting business intelligence is consumed, interpreted and acted upon by the business.
You are a passionate advocate for your customer. In addition to metrics definitions, you learn the business context and technologies behind your team’s data infrastructure. You work effectively with customers (e.g., business teams, Data Scientists, etc.) and other internal partners to ensure deliverables are aligned with expectations.
You invent, refine and develop your BI solutions to ensure they are meeting the needs of the business and team goals.
- 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)
- Master's degree, or Advanced technical degree
- Knowledge of data modeling and data pipeline design
- Experience with statistical analysis, co-relation analysis
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
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Amazon runs the largest online store in the United States and rents cloud computing to businesses and governments through Amazon Web Services. AWS pioneered renting computing power over the internet, and Amazon built its own delivery network to get orders to customers quickly. Shoppers buy from Amazon and from independent sellers on its store, and Prime members pay a subscription for fast free shipping, streaming video and music, and other perks. AWS rents out computing power, storage, databases, and AI tools so companies can run software without owning servers, and Amazon also makes Kindle e-readers and Echo speakers with the Alexa assistant. Jeff Bezos founded Amazon in 1994, and it is based in Seattle, Washington.
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