Business Intelligence Engineer, Supply Chain, Supply Chain Placement And Crossdock

DESCRIPTION The Supply Chain team is looking for a Senior Business Intelligence Engineer, as part of the Supply Chain analytics team. You will contribute to defining and building inventory placement success metrics, and finding ways to reduce distance to customers by placing the right items in the right Amazon building in order to increase delivery speed and reduce costs. You will chase defects in our systems, leaving no stone unturned to delight our customers with wider selection. This role will give you a unique view on Amazon systems, process and operations, interacting with planning teams, fulfillment centers and worldwide technical teams. If you are someone who has shown success in analyzing, diving deep in complex data, streamlining and identifying process improvement opportunities and pioneering new ways to do things, we'd like to talk to you.
Key job responsibilities
You will lead some critical performance management initiatives for inventory placement WW leveraging complex data management/visualization and presenting those to different levels within the company:
- Design and own the right set of metrics measuring inventory placement performance
- Recommend improvements to the placement strategy using modelling and large datasets. You'll guide planning teams and other relevant stakeholders with regards to the mix of products to place in Amazon buildings, maximizing selection and reducing distance to customers and spinning the Amazon flywheel!
- Pioneer new ideas to increase speed and reduce delivery cost to customers
- Pilot and implement your recommendation in production through smart configurations in Amazon systems
- Develop the analytics required to visualize opportunities and measure progresses
- Partner with worldwide technical teams to develop new features
We are open to hiring candidates to work out of one of the following locations:
Bellevue, WA, USA | New York, NY, 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