- 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
Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $89,600/year in our lowest geographic market up to $185,000/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.
At Amazon we believe that every day is still day one. We are working to be the most customer-centric company on earth. To get there, we need exceptionally talented, bright, and driven people.
As a Business Intelligence Engineer, you will generate insights that will guide operational excellence and business strategy for our customers. Data analysis is at the core Amazon’s culture, and your work will have a direct impact on decision making and strategy for our organization. You will be gathering customer insights, mining data, making recommendations, and helping senior leaders make key business decisions. The ideal candidates will have excellent analytical abilities, outstanding business acumen and judgment, intense curiosity, strong technical skills, and superior written and verbal communication skills. They will have a strong bias toward data driven decision making. They will be a self-starter, comfortable with ambiguity, able to think big and be creative (while paying careful attention to detail). Enjoys working in a fast-paced dynamic environment. If you are excited about data, are results oriented, and want to join a growing analytics team within Amazon, this role is for you.
Key job responsibilities
- Supporting strategic project planning, leveraging data to deliver insights, and deep dive on projects.
- Designing, developing and managing tools to support ongoing business reporting. Working with global Business Intelligence counterparts to develop the data pipeline and metric definitions. Building out business dashboards, visualization tools, and finance reports.
- Supporting continuous business performance optimization by designing and driving experiments to form actionable recommendations. Presenting recommendations to business leaders to drive decisions.
- Design, develop and maintain scaled, automated, user-friendly systems, reports, dashboards, etc. that will support the needs of the business.
- Apply deep analytic and business intelligence skills to extract meaningful insights and learning from large and complicated data sets.
- Be hands-on with ETL to build data pipeline to support automated reporting.
- Serve as liaison between the business and technical teams to achieve the goal of providing actionable insights into current business performance, and ad hoc investigations to support future improvements or innovations. This will require data gathering and manipulation, problem solving, and communication of insights and recommendations.
- Build various data visualizations to tell the story of business trends, patterns, and outliers through rich visualizations.
- Recognize and adopt best practices in reporting and analysis: data integrity, test design, analysis, validation, and documentation.
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