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Business Intelligence Engineer II, Centralized Data and Insights
1 month ago
Amazon Web Services (AWS) is seeking a highly skilled Business Intelligence Engineer II to join our Centralized Data and Insights team. As a key member of our team, you will be responsible for designing, developing, and implementing scalable data processing solutions using multiple platforms.
The ideal candidate will have a strong background in data analysis, data visualization, and business intelligence. You will work closely with cross-functional teams to gather and understand data requirements, and develop high-quality and scalable data solutions for our products and mechanisms.
Key Responsibilities:
- Implement data pipelines from disparate sources to ingest, transform, and store data in a scalable format.
- Gather and understand data requirements, working with cross-functional teams to achieve high-quality and scalable data solutions.
- Develop and present recommendations for new metrics to improve understanding of business performance.
- Design and implement data visualizations using Tableau, Quicksight, or similar tools.
About the Team
The Centralized Data and Insights team is a dynamic and innovative group of professionals who are passionate about using data to drive business insights. We are looking for a talented Business Intelligence Engineer II who is eager to learn and grow with our team.
What We Offer
- A competitive salary and benefits package.
- The opportunity to work with a talented team of professionals in a dynamic and innovative environment.
- Professional development opportunities, including training and mentorship.
Requirements
- 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.
- Experience developing and presenting recommendations for new metrics to improve understanding of business performance.
Preferred Qualifications
- Experience with AWS solutions such as EC2, DynamoDB, S3, and Redshift.
- Experience in data mining, ETL, and using databases in a business environment with large-scale, complex datasets.
- Scripting experience (e.g. Python) for data analysis.
