Amazon Business Intelligence Engineer Infrastructure 

United States, Washington, Seattle 

983510715

You will have a passion to dive deep, a high level of customer focus and a track record in process improvement. This role requires an individual with excellent analytical abilities, strong knowledge of business intelligence solutions and the ability to work with Finance, quantitative and business teams. You will lead multiple automation and controllership initiatives across the Finance org. You will be primarily using but not limited to AWS solution stacks like Redshift, S3, Glue, Data pipeline and reporting tools such as Tableau and Alteryx/KNIME to implement BI solutions.Key job responsibilities
- Develop and implement scalable and reliable analytics, tools, KPI dashboards, and metrics that drive key supply chain, financial, and procurement decisions.
- Design and implement metrics dashboards to deepen understanding of cost structures, capital spend, and variances highlighting opportunities for improvement.
- Collaborate with Finance, Tax, Supply Chain, Procurement, and Engineering to capture requirements and deliver analytics solutions.
- Develop and implement analytics to continually improve continuity of supply and operational efficiencies.
- Apply automation so that with every iteration on a problem, you build your solution to have maximum scale and self-service ability by stakeholders.- Recognize and use advanced analytical techniques to recommend prescribed/ optimized courses of action to users.
- Participate in strategic and tactical planning discussions to interface with business customers, gathering requirements and delivering complete reporting solutions.

- 2+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL etc. experience
- Experience with data visualization using Tableau, Quicksight, or similar tools
- Experience with one or more industry analytics visualization tools (e.g. Excel, Tableau, QuickSight, MicroStrategy, PowerBI) and statistical methods (e.g. t-test, Chi-squared)
- Experience with scripting language (e.g., Python, Java, or R)

- Master's degree, or Advanced technical degree
- Knowledge of data modeling and data pipeline design
- Experience with statistical analysis, co-relation analysis