Amazon Business Intelligence Engineer DSCL BI 

United States, California, Sunnyvale 

829903415

You should have expertise in designing, implementing, and operating stable, scalable, low cost solutions to flow data from production systems into the data warehouse and into end-user facing applications. You should be able to work with business customers in a fast paced environment understanding the business requirements and implementing reporting solutions.
Key job responsibilities
• Engage with leadership and diversified functional groups to understand the needs and recommend business intelligence solutions.
• Own the design, implementation, and maintenance of ongoing metrics, reports, analyses, and dashboards, to drive key business decisions.
• Partner with technology teams to define, extract, transform, and load data from many data sources using SQL and other tools.
• Automate and simplify self-service or reporting pipelines, including improving ETL workflows, automatic alarming and performance tuning.
• Conduct deep dive analyses of business problems and data issues and formulate conclusions and recommendations for leadership and technical teams
• Participate in strategic and tactical planning discussions and provide data insights. Challenge business teams to think differently about how they digest and use the data insights to make informed decisions.
• Make recommendations for new metrics, techniques, and strategies to improve business KPI's
• Be connected and influential within the Amazon BIE community. Work with Data engineering, Software development teams to enable the appropriate capture and storage of key data points.AI-Related Responsibilities:
• Develop and implement AI/ML models to enhance predictive analytics capabilities and automate decision-making processes
• Lead the integration of generative AI tools to streamline reporting workflows and improve data visualization
• Design and implement AI-powered anomaly detection systems for early identification of business metrics deviations
• Create intelligent automation solutions using AI to reduce manual effort in routine data analysis tasks
• Partner with AI/ML teams to develop and deploy custom machine learning solutions for business-specific use cases
• Stay current with emerging AI technologies and evaluate their potential application in improving BI processes
• Build and maintain AI-driven self-service analytics platforms to democratize data access across the organization
A day in the life
* Understand a broad range of Supply Chain & Logistics data resources/processes
* Partner with internal stakeholders across multiple teams, gathering requirements and delivering end to end solutions
* Partner with Data Engineering and Software Development Engineers to define data and BI development needs
* Conduct deep dive analyses of business problems and formulate conclusions and recommendations; determine optimized courses of action to deliver comprehensive BI solutions.
* Synthesize requirements into technical specifications to solve ambiguous business problem and outline Analytics solution
* Design, develop and maintain scalable and reliable analytical tools, dashboards, and metrics that drive key business decisions
* Simplify and automate reporting, metrics and dashboards; build solutions to have maximum scale and self-serviceability by users
* Recognize and adopt best practices in reporting and analysis: data integrity, test design, analysis, validation, and documentation
* Handle multiple projects at once, deal with ambiguity and rapidly-changing priorities

- 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 writing complex SQL queries
- Experience using SQL to pull data from a database or data warehouse and scripting experience (Python) to process data for modeling
- Bachelor's degree in BI, finance, engineering, statistics, computer science, mathematics, finance or equivalent quantitative field