Amazon Web Services (AWS) · 1 week ago
Business Intelligence Engineer
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Responsibilities
Lead sales executive discussions to share insights, challenge status quo, and provide forward looking recommendations to enable growth of Private Pricing.
Support the development of a continuously-evolving business analytics and data models, own the quantitative analysis of the performance of our sales team, customers, deal team, partners, markets, and products/services.
Develop a deep understanding of sales metrics, reporting tools, and data structures in order to identify and drive resolution of issues, provide actionable intelligence with existing metrics or identify, develop, and propose new metrics, dashboards, scorecards or new tools.
Develop relationships and processes with sales, finance, sales operations, and other functional teams to identify and address reporting issues.
Manage and develop analytical tools or reports that align, and simplify, monthly business reviews, annual planning, and forecasting processes.
Create operational templates and processes to compile and standardize disparate information that drive standardized reporting and metrics tracking.
Work with regional teams to deconstruct issues and develop solutions that help meet financial and operational goals.
Generate ad-hoc and monthly operational analysis and reports, based on the needs of the stakeholders.
Provide actionable recommendations through ad-hoc data retrieval and analysis from data management systems.
Create new mechanisms and business processes that simplifies, standardizes and enables operational excellence.
Qualification
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Required
3+ 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 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
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
Benefits
Flexible schedule
Mentorship programs
Career growth opportunities
Company
Amazon Web Services (AWS)
Launched in 2006, Amazon Web Services (AWS) began exposing key infrastructure services to businesses in the form of web services -- now widely known as cloud computing.
Funding
Current Stage
Late StageLeadership Team
Recent News
2024-06-01
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