Sr. Business Intelligence Engineer, B2C, Amazon Leo

About the role

The Sr. Business Intelligence Engineer will build the analytics and data foundations that power Amazon Leo's global marketing engine. This role is critical in defining how a new Amazon business measures customer behavior, marketing effectiveness, funnel performance, and growth.

Responsibilities

• Architect, build, and maintain foundational business datasets across our tech stack and other internal systems to support analytics, reporting, and customer growth use cases.
• Develop SQL-based transformations, data models, and ETL/ELT workflows to structure and unify marketing and customer data for customer lifecycle use cases.
• Design, optimize, and manage Amazon QuickSight dashboards that provide visibility into acquisition performance, attribution, and lifecycle funnels.
• Conduct deep-dive analysis to identify funnel drop-offs, diagnose performance issues, uncover customer insights, and evaluate marketing effectiveness.
• Translate ambiguous business questions into structured analytical approaches, data models, and scalable self-service tools.
• Drive alignment on KPI definitions, measurement frameworks, taxonomy, and data governance across global marketing teams.
• Collaborate closely with Product, Sales Ops, Data Science, and cross-functional partners to support experimentation, segmentation, forecasting, and predictive insights.
• Communicate effectively with senior management audiences (e.g., narratives, inputs into weekly/monthly/quarterly business reviews).
• Drive best practices in operational excellence, data modeling, and analysis. Ensure that BI solutions are correctly and efficiently supporting the business.
• Participate in hiring activities and mentor junior team members

Qualifications

• 6+ years of professional or military experience
• 5+ years of SQL experience
• 1+ years of SQL, ETL or Oracle experience
• 1+ years of processing large, multi-dimensional datasets from multiple sources experience
• 1+ years of performing statistical analysis experience
• 1+ years of developing automated reporting experience
• Experience programming to extract, transform and clean large (multi-TB) data sets
• Experience with theory and practice of design of experiments and statistical analysis of results
• Experience with AWS technologies
• Experience with theory and practice of information retrieval, data science, machine learning and data mining