7+ years of business intelligence and analytics experience
5+ years of delivering results managing a business intelligence or analytics team, including employee development and performance management experience
Experience with SQL
Experience with ETL
Experience with data visualization using Tableau, Quicksight, or similar tools
Experience with R, Python, Weka, SAS, Matlab or other statistical/machine learning software
4+ years of working with very large data warehousing environment experience
10+ years of data warehouse technical architectures, data modeling, infrastructure components, ETL/ ELT and reporting/analytic tools and environments, data structures and hands-on SQL coding experience
Experience working directly with business stakeholders to translate between data and business needs
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Additional Information
Amazon Advertising's Support Products & Services (SP&S) team is building the AI-powered future of advertiser support at massive scale. We're not just answering questions - our AI agents execute multi-step agentic workflows, automate the majority of common customer support use cases, and are featured prominently in the Amazon Advertising console, serving millions of advertisers worldwide.
SP&S is seeking a highly experienced Business Intelligence Manager to lead the design, development, and scaling of advanced analytics, data infrastructure, and decision science capabilities across our large, complex business domain. This role defines the analytics vision, drives cross-organizational data strategy, and delivers scalable BI systems that power critical business decisions at SP&S. As our AI development accelerates, Business Intelligence is becoming core infrastructure - not a supporting function. We are shifting from bespoke, one-off data solutions to building reusable data pipelines, shared analytics capabilities, and measurement frameworks that power every agent team we spin up.
We are looking for a BI Manager to lead and grow our BI and analytics team. You will be a player-coach: personally contributing hands-on to our most technically demanding data engineering work while providing the technical oversight, prioritization, and career development that enables our team to scale. You will lead a team of high-performing Business Intelligence Engineers, Data Engineers, Data Scientists and Business Analysts supporting a rapidly expanding AI product roadmap. You will own the full scope of our data needs: building and maintaining the pipelines that power our AI agents, creating the measurement frameworks that define how we track advertiser support and business impact, and ensuring our BAU reporting commitments are met without crowding out strategic infrastructure work. This is a high-impact, high-visibility role - you will be a primary technical partner to Product and Leadership and will be expected to set the standard for how BI is done across our org as we scale.
The ideal candidate is a technically exceptional BI leader who is passionate about using data and thrives in dynamic, ambiguous environments where the roadmap is evolving. You think big about what BI infrastructure can enable - not just for today's needs, but for the AI-powered experiences your organization is building toward - while maintaining a relentless bias for action that keeps the team moving. You earn trust through your craft: writing clean, scalable pipelines; designing measurement frameworks that hold up to scrutiny; and communicating technical complexity clearly to Product and Program stakeholders who depend on your judgment. You invent and simplify, always asking whether a shared, reusable solution can replace a one-off build.
Key job responsibilities
- Define long-term analytics vision for SP&S and partner with senior leadership to influence business strategy, roadmaps, and metric standardization through data-driven insights.
- Translate ambiguous business problems into scalable analytical frameworks and data solutions enabling high-impact decision-making.
- Design and oversee large-scale data models, semantic layers, and distributed systems (S3, Redshift, Spark, EMR, Glue) with strong focus on performance, governance, and data quality.
- Apply causal inference, experimentation (A/B testing) etc., models to uncover insights, drive statistical rigor, and influence executive decisions.
- Champion best practices (SQL, Python, ETL), drive self-serve and AI-enabled analytics, and mentor/hire BIE/DE talent to build a high-performing data organization.
Amazon.com · Seattle, WA