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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Sr BIE, ASP Business Intelligence - **Company:** Amazon.com, Inc. - **Location:** Seattle, WA, United States - **Experience:** Expert - **Salary:** $130,400.0 - $176,300.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Amazon Web Services, Business Analytics Applications, Information Engineering, Data Systems, Software Design Documents, Graph Database, Python (Programming Language), Machine Learning, Performance Tuning, Scripting, Sql Optimization, Large Language Models, Multi-Agent Systems, Information Technology, Data Management, Data Pipelines, Api Management, Legacy Systems - **Published:** August 22, 2026 - **Apply:** https://www.amazon.jobs/en/jobs/10509647/sr-bie-asp-business-intelligence ## About the Role 7+ years of as a Data Analyst, Data Engineer, Business Intelligence Analyst, or a related occupation experience - Experience in scripting for automation (e.g. Python) and advanced SQL skills. - Bachelor's degree or foreign equivalent in Computer Science, Engineering, Mathematics, Statistics, Economics, or a related field - Experience architecting and owning end-to-end data platforms serving multiple downstream consumers - Track record of driving technical decisions with cross-team impact, Experience building or integrating AI/ML capabilities into data platforms or analytics products (LLMs, RAG, agent frameworks, knowledge graphs, or similar) - Experience designing governance or quality frameworks for data consumed by automated systems - Experience defining tooling strategy for a team - evaluating options, building shared infrastructure, and establishing reusable patterns - Track record of building automated analytics systems (autonomous reporting, intelligent alerting, self-service interfaces) - Strong systems thinking - ability to see upstream/downstream impact across a complex data ecosystem ## Description AWS is seeking a Senior Business Intelligence Engineer III to lead analytics strategy for the Specialist Insights team, focused on Data and AI. This team operates at the intersection of data engineering and AI - building systems where intelligent automation handles the default case and human expertise focuses on exceptions, strategy, and novel problems. Working closely with Data and AI Sales Operations leadership, the Senior BIE owns the end-to-end analytics architecture: data platforms, governance frameworks, self-service products, and the integration points where AI capabilities plug into the stack. This role defines how the team builds, sets technical standards others follow, and drives the evolution from traditional reporting toward systems that learn and scale. The ideal candidate has deep data engineering fundamentals, has worked with AI/ML in production or near-production contexts, and treats system design and organizational influence as equal parts of the job. Key job responsibilities * Owns the architecture and technical roadmap for the team's analytics systems - data platforms, governance layers, self-service products, and the integration patterns that connect them to AI-powered downstream applications. * Designs and drives implementation of scalable data platforms: pipeline orchestration, automated quality monitoring, schema management, and infrastructure that supports both traditional BI and AI-native consumption patterns. * Architects governance frameworks that maintain data trust at scale: lineage, freshness enforcement, validation pipelines, ownership models, and content lifecycle practices - especially as AI systems become consumers of the team's data. * Builds and owns automated analytics systems - report generation, KPI monitoring, anomaly detection, insight delivery - designing for progressive automation where AI handles the routine and humans handle the exceptions. * Defines the team's AI tooling strategy: evaluates frameworks, builds shared infrastructure (prompt libraries, evaluation patterns, integration templates), and establishes practices that help the whole team work effectively with AI. * Drives cross-functional alignment on data product architecture; influences partner teams on integration patterns, API contracts, and standards for how data products interoperate across the ecosystem. * Makes technical decisions with broad impact: data modeling trade-offs, build-vs-buy on capabilities, migration strategies from legacy systems, and cost/performance optimization across the stack. * Applies advanced statistical and ML methods within production systems; ensures analytical rigor in automated outputs and designs experimentation frameworks that quantify business impact. * Mentors and levels up the team on data engineering craft, system design, governance thinking, and practical AI/ML application - raising the bar for what the team can build and maintain. * Communicates complex technical architecture and strategy to senior leadership; writes design documents that drive alignment, presents trade-offs clearly, and translates technical capability into business outcomes. ## Related Videos - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [JavaScript? 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