Business Intelligence Engineer, Supply Chain Data Science
at Amazon
Posted 6 hours ago
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Join Amazon's supply chain analytics team as a Business Intelligence Engineer focused on data science for logistics. You will design end-to-end data pipelines, harmonize multiple data sources, and develop dashboards and automated insights to guide decision-making. You will write high-quality SQL, work with Python/R, and create ad-hoc visualizations to inform optimization and simulation efforts across a complex logistics network. You will collaborate with product, data science, software engineers and partner teams to translate business questions into scalable data solutions.
Amazon’s extensive logistics system is comprised of 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 unparalleled. This magnificent challenge is a terrific opportunity to analyze Amazon’s data and generate actionable recommendations using optimization and simulation. Come build with us!
This role will collaborate with diverse set of stakeholder including product managers, program managers, data scientists, software development engineers and other partner teams to analyze large data sets, prove and disprove hypothesis, automate existing solutions and build self-service dashboards and reports.
Key job responsibilities
E2E design and creation of data pipelines including harmonization of different data sources (Data base, API, user inputs and manual files) using SQL and other scripting language (R,Python,Rust), reporting and automation using Quicksight tableu or similar. Design of automations to send push out information of alerts, business insights etc. Project and stakeholder management
Write high quality SQL code to retrieve and analyze data from database tables, and learn and understand a broad range of Amazon’s data resources and know how, when, and which to use and which not to use.
Develop queries and visualizations for ad-hoc requests and projects, as well as ongoing reporting.
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
- Speak, write, and read fluently in English, and have the ability to take direction in English
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
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