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Business Intelligence Engineer, Sustainability Strategist

2 months ago

Seattle, Washington, United States Amazon Full time
About the Role

We are seeking a highly skilled Business Intelligence Engineer to join our Worldwide Sustainability team at Amazon. As a key member of our team, you will play a critical role in developing analytical solutions for measuring and reporting on Amazon's global footprint impact areas.

Key Responsibilities
  • Deliver High-Impact Data Visualization Solutions: Design and implement data visualization solutions to measure and report on Amazon's global carbon, waste, and water footprints.
  • Support Cross-Functional Teams: Collaborate with internal teams to develop and maintain metric tables, interactive dashboards, and data pipeline alarms.
  • Provide Data Insights and Support: Offer ad-hoc data extraction and assessment support to program teams tasked with reporting on business unit activities and external disclosures.
  • Lead Reporting on User Engagement and Customer Sentiment: Develop and lead reporting on user engagement and customer sentiment across all WWS products.
About the Team

Our team values diverse experiences and is committed to creating an inclusive culture. We believe that our employee-led affinity groups foster a culture of inclusion that empowers us to be proud of our differences. We prioritize work-life harmony and offer flexible work hours and arrangements to support our employees' well-being.

Requirements
  • 3+ years of experience analyzing and interpreting data with Redshift, Oracle, NoSQL, etc.
  • 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.
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.