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.
About the team
About AWS
Diverse Experiences
AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.
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Work/Life Balance
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4+ years of SQL, ETL or Oracle experience
4+ years of processing large, multi-dimensional datasets from multiple sources experience
4+ years of developing automated reporting experience
Bachelor's degree or foreign equivalent in Computer Science, Engineering, Mathematics, Statistics, Economics, or a related field
Experience with data visualization using Tableau, Quicksight, or similar tools
Experience in scripting for automation (e.g. Python) and advanced SQL skills.
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.
USA, TX, Austin - 130,400.00 - 176,300.00 USD annually
USA, TX, Dallas - 130,400.00 - 176,300.00 USD annually
USA, WA, Seattle - 130,400.00 - 176,300.00 USD annually
