Key job responsibilities
Define the customer and map the journey. Build the data models and analytical frameworks that give CXP a unified view of the customer journey across every channel (chat, voice, home page).
Build the data foundation for personalized support. Own the curated data products (customer profiles, interaction histories, intent signals, resolution patterns) that enable CXP to tailor the experience based on customer context.
Own the technical architecture and roadmap for CXP's analytics data ecosystem, including pipeline orchestration, schema design, data quality monitoring, and the integration layer feeding BI and AI/ML systems.
Operationalize "data as a product" with clear ownership, freshness SLAs, lineage, and governance standards that scale across multiple director organizations.
Drive metric integrity by establishing canonical definitions, reconciling data sources, and building validation frameworks leadership can trust.
Lead cross functional alignment with Science, Product, and Engineering teams on data modeling standards and integration patterns.
Make high judgment technical decisions on modeling trade offs, build vs. buy, and cost/performance optimization.
Mentor and raise the bar for a team of BIEs in analytics best practices, governance, and AI/ML application.
Communicate strategy to Director and VP level leadership through narratives and design documents.
10+ years of business intelligence and analytics experience
Experience in building analytic or scientific data products or solutions
Experience building measures and metrics, and developing reporting solutions
Experience coding in scripting languages such as Python, R, Matlab, or STATA
Experience in Redshift, or experience in Hive/Spark/Hbase/Yarn and experience in any Bigdata architecture
Bachelor's degree in Computer Science, Engineering, Mathematics, Statistics, Economics, or a related field
Master's degree in an advanced technical degree field
5+ years of working with Data & AI related technologies, including, but not limited to, AI/ML (Artificial Intelligence/Machine Learning), GenAI (Generative AI), Analytics, Database, and/or Storage experience
Experience in data warehouse technical architectures, data modeling, infrastructure components, ETL/ ELT and reporting/analytic tools and environments, data structures and hands-on SQL coding
Experience building cross-functional partnerships and influencing stakeholders across the organization to act without having a direct reporting relationship
Experience in written and verbal communication with the ability to present complex technical information in a clear and concise manner to executives and non-technical leaders
Experience with customer journey analytics or customer experience domains
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, WA, Seattle - 155,100.00 - 209,800.00 USD annually
