Business Intelligence Engineer, GFP Analytics (GFPA)

Description Have you ever ordered a product on Amazon and wondered how that package got to you so fast? Have you ever wondered where it came from and what series of events helped make that delivery possible? If so, the Global Fleet and Products Analytics team is for you! We (GFPA) work with large amounts of novel data and provide insights that help deliver billions of packages to customers every year. We focus on everything from high-level strategic support, to strategic initiatives (e.g., Electrification), down to granular insights that drive entitlements, operational excellence, safety outcomes, or fleet-based efficiencies. The GFPA team is looking for a BIE to shape how we use data to support a wide range of strategic initiatives in the Last Mile space. As a BIE on our team, you will develop and lead new technical solutions, influence business critical decision-making with massive scale, and influence multiple organizations and geographies. To be successful in this role, you'll need to be an excellent time, project, and customer manager, great communicator, and problem solver extraordinaire. You'll work on complex initiatives that have never been solved before. Excellent candidates will be able to work with a high degree of ambiguity and use data/analytic engineering to drive meaningful changes. This role may be located out of Austin, Nashville, or Seattle. In this position you will: - Provide strategic advisory to business teams and leaders that liaise technical and business needs. - Engineer critical input and output metrics - Create performance metrics to measure operational performance, identify root causes and trends, and prescribe action plans for delivery stations around the globe - Manage metrics across multiple projects simultaneously - Work with product, technology, and analytics teams to support the development of tools and dashboards - Communicate with and support various internal stakeholders and external audiences - Learn, explore, apply, and gain expertise in many internal Amazon data and public AWS products including Glue, Redshift, Quicksight, and Lambda 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 Preferred Qualifications - 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 Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us. Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $89,600/year in our lowest geographic market up to $185,000/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.