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Amazon Business Intelligence Engineer Amazon Finance Analytics United States, Washington, Seattle 763931167
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Key job responsibilities
Develop Analytical Systems and Tools:Collaborate with Cross-Functional Teams:
Partner with data engineers, business stakeholders, and other cross-functional teams to gather requirements, establish new data pipelines, and deliver complete, insightful solutions. Foster collaboration to drive results and implement innovative solutions.
Optimize Data Performance:
Tune application and query performance using SQL and other relevant technologies. Ensure the reliability, performance, and scalability of reporting models, data pipelines, and databases.
Perform Advanced Data Analysis:Automate and Simplify Reporting Processes:
Simplify and automate reporting and other data-driven activities. Develop self-service automated reporting processes and deep-dive tools to enable stakeholders to access and understand data with ease.
Ensure Data Integrity and Best Practices:
Establish and adopt best practices in data modeling, reporting, and analysis. Ensure data integrity, test design, analysis, validation, and documentation are maintained to the highest standards.
Provide Strategic Insights and Recommendations:A day in the life
As a BI Engineer in Amazon Business, you will work in one of the world's largest cloud-based data lakes. You will dive deep into big datasets with an expectation to deliver the best analytics and insights to senior business, technical, and finance leaders. You will partner with all areas of AB (from Technology to Sales, from Pricing to Marketing) to provide the data and models that are needed to drive decision making. You must be a self-starter and be able to learn on the go. Excellent written and verbal communication skills are required as you will work with diverse teams.
BASIC QUALIFICATIONS
- Experience with data visualization using Tableau, Quicksight, or similar tools
- 3+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL etc. experience
- 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
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