Amazon

Business Intelligence Engineer I

Job Description

Amazon is seeking a Business Intelligence Engineer (BIE) to support Vendor Investigation and Transaction Accuracy (VITA). VITA’s mission is to detect and prevent theft, fraud, abuse and waste globally. We use advance techniques to prevent erroneous payments and to protect Amazon shareholders. We are seeking a BIE to support our automation and data needs. The ideal candidate thrives in a fast-paced environment, relishes working with large transactional volumes and big datasets, and is passionate about data and analytics. BIE L4 is focused on developing and maintaining small to mid-size BI solutions or components of larger solutions. Their primary sphere of influence extends within their immediate team, where they deliver data-driven solutions that directly inform team business decisions.
The core technical requirements demand proficiency in SQL and data manipulation, along with the ability to create and maintain ETL processes. They should be capable of building data structures using schema definition languages and demonstrate competence with analytics visualization tools such as Excel, or QuickSight. The role requires practical application of descriptive statistics and basic inferential statistics in data analysis. BIE L4 builds and maintains various data artifacts including ETL processes, data models, and queries. They create reports that accurately answer business questions while ensuring their code is secure, stable, testable, and maintainable. A key aspect of their role involves automating manual processes where possible and thoroughly validating outputs against source data and business logic.
BIE L4 must submit their analyses and code for review, conduct thorough testing, and handle data in accordance with Amazon policies. They are responsible for investigating data anomalies, troubleshooting issues, and either resolving them or ensuring proper handoff to the appropriate owner


Key job responsibilities
• Translate business risks and needs into the development of analytics for fraud and risk detection
• Coordinate with technical teams as appropriate to develop and implement analytics and reporting needs
• Partner with stakeholders to gather requirements and integrate necessary data sources to support business analysis and reporting
• Has quantitative or engineering background
• Understands how to use one or more industry analytics and metrics visualization tools (e.g. QuickSight).
• Proficiency in SQL.
• Knowledgeable in a variety of methods for querying, processing, persisting, analyzing and presenting data.
• Understands one or more schema definition languages (e.g. DDL, SDL, XSD, RDF).
• Has a good understanding of data lineage: including sources of data; how metrics are aggregated; and how the resulting business intelligence is consumed, interpreted and acted upon by the business.
• Proficient in descriptive statistics (i.e. measures of distribution). You are familiar with inferential statistics (e.g. hypothesis testing, confidence intervals) and know when such methods are appropriate.
• Knowledgeable in methods for identifying trends in metrics. Able to segment metrics along suitable dimensions to reveal deeper dynamics.
• Able to dive deeply into technical and operational details of the business (e.g., key dependencies, business drivers/KPIs, develop actionable business insights, etc.) and contribute to a constructive technical discussion.
• Coordinate with global team members to conduct deep dives walk-throughs and quality reviews of evidence to resolve complex problems.
- 2+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL etc. experience
- Experience with data visualization using Tableau, Quicksight, or similar tools
- Experience with one or more industry analytics visualization tools (e.g. Excel, Tableau, QuickSight, MicroStrategy, PowerBI) and statistical methods (e.g. t-test, Chi-squared)
- Experience with scripting language (e.g., Python, Java, or R)


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