Business Intelligent Engineer II, Ship With
2 days ago
Our customers have immense faith in our ability to deliver packages timely and as expected. A well planned network seamlessly scales to handle millions of package movements a day. It accurately forecasts the package movements across the network, has monitoring mechanisms that detect failures before they even happen (such as predicting network congestion, operations breakdown). When failures do happen, it has inbuilt redundancies to mitigate impact (such as determine other routes or service providers that can handle the extra load), and avoids relying on single points of failure (service provider, node, or arc). Finally, it is cost optimal, so that customers can be passed the benefit from an efficiently set up network.
Amazon Shipping (SWA) is hiring Business Intelligence Engineer (BIE) to enhance the pick-up experience and reduce first-mile costs. As a BIE at SWA, you will lead the data and reporting requirements for First Mile and Pickup programs. Your role will involve close engagement with senior leaders to generate insights and conduct deep dives into key metrics that directly influence organizational strategic decisions and priorities. You will demonstrate a high proficiency in complex SQL scripting, often combining various data sets from diverse sources. You will contribute to projects to improve Volume Forecasting and Capacity Panning. You will own the design, development, and maintenance of ongoing metrics, reports, dashboards, etc. to drive key business decisions. You will simplify and automate reporting, audits, and other data-driven activities. You will partner with Data Engineering to enhance data infrastructure, data availability, and broad access to customer insights. You will develop and drive best practices in data integrity, consistency, validations, and documentation.
You will work as part of a diverse data science and engineering team comprising of Applied Scientists, Software Development Engineers, and other BIEs.
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
- Experience with AWS solutions such as EC2, DynamoDB, S3, and Redshift
- Experience in data mining, ETL, etc. and using databases in a business environment with large-scale, complex datasets
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