Business Intel Engineer Ii, Receive Accuracy

DESCRIPTION Amazon's Receive Accuracy team is looking for motivated individuals with strong analytical skills to evolve one of the most complex supply-chain systems in the world.
Amazon's supply-chain comprises thousands of fixed infrastructure nodes with millions of possible connections between them. Billions of packages flow through this network on a yearly basis, making the impact of optimal improvements truly innovative. This job offers is a terrific opportunity to analyze Amazon data and understand, model, optimize, and reshape Amazon's Receive Accuracy.
As a Business Intelligence Engineer, you will generate insights that will guide feedback to operators and business strategy decisions. Data analysis is at the core Amazon's culture, and your work will have a direct impact on decision-making and strategy for our organization. You will be gathering operational insights, running statistical analysis, mining data, making recommendations, visualizing data, and helping senior leaders make key business decisions.
You should be enthusiastic about leveraging data to uncover insights and solve business problems for Receive Accuracy stakeholders, by producing end-to-end business intelligence solutions. Such solutions require data querying, data pipelining, and data visualization/dashboard building. You should also be enthusiastic about building deep domain knowledge about Amazon's business and the fulfillment space. This role requires an individual with excellent analytical abilities as well as outstanding business acumen and comfort with technical teams and systems. The successful candidate will be a self-starter comfortable with ambiguity, with strong attention to detail, and enjoys working with large datasets.
We are open to hiring candidates to work out of one of the following locations:
Arlington, VA, USA | Bellevue, WA, USA | Nashville, TN, USA | Seattle, WA, USA BASIC QUALIFICATIONS - 3+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL etc. experience
- Experience with data visualization using Tableau, Quicksight, or similar tools
- Experience with data modeling, warehousing and building ETL pipelines
- 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