Business Intelligence Engineer
1 month ago
We are seeking a highly skilled Business Intelligence Engineer to join our Global Operations team. As a key member of our team, you will be responsible for designing, developing, and maintaining scaled, automated, user-friendly systems, reports, and dashboards to support our analytical and business needs.
Key Responsibilities- Use analytical and statistical rigor to solve complex problems and drive business decisions that will help us achieve our strategic goals.
- Design, develop, and maintain automated systems, reports, and dashboards to support our analytical and business needs.
- Ability to invent, refine, and develop BI solutions to ensure they meet the needs of the GO-AI goals.
- Ability to maintain and refine straightforward ETL and create, populate data structures using one or more schema definition languages.
- Focus on operational excellence: constructively identifying quality issues, proposing solutions when necessary, taking on projects that improve your team's BI solutions.
- Good understanding of the relevant data lineage: including sources of data; how metrics are aggregated; and how the resulting business intelligence is consumed, interpreted, and acted upon by the business.
The Global Operations - AI (GO-AI) team handles exceptions remotely in the Amazon Robotic Fulfillment Centers Globally. GO-AI seeks to complement automated vision-based decision-making technologies by providing remote human support for the subset of tasks that require higher cognitive ability and cannot be processed through automated decision making with high confidence.
Requirements- 5+ 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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