Prime Video is changing the way customers watch movies, TV shows, live events, and channels—offering unparalleled choice and convenience across devices such as Fire TV, mobile phones, game consoles, and connected TVs. We deliver world-class viewing experiences to customers in over 240 countries and territories.
The Prime Video Product Analytics (PVPA) team is a centralized analytics organization supporting the Prime Video Product organization. We bring together Business Intelligence Engineers, Data Engineers, and Data Scientists to deliver comprehensive data tools and insights that drive product decisions and enhance customer experience. Our work spans the full analytics lifecycle—from data infrastructure and pipeline development to advanced analytics, customer insights modeling, AI-driven solutions, and self-service reporting.
This role sits within the PVPA team focused on out-of-app engagement and full-funnel customer journey analytics. Our mission is to understand and optimize how customers discover, engage with, and return to Prime Video—connecting off-app marketing touchpoints (such as email, push, a.com, WhatsApp, search engines, and paid media) with in-app behavior and engagement to build a complete, end-to-end view of the customer experience. We harness data across this full funnel—from acquisition and onboarding through long-term retention—to inform personalization, measure customer engagement and channel effectiveness, and deliver the right content to the right customer at the right time.
Key job responsibilities
We are looking for a highly motivated and experienced Business Intelligence Engineer (BIE) II to join the PVPA team. In this role, you will play a key part in driving customer understanding through data.
You will design and build scalable analytics solutions, self-service reporting tools, and experimentation frameworks, increasingly powered by AI and automation, that give stakeholders across product, marketing, and science a deep, reliable understanding of customer behavior. Your work will directly inform how Prime Video acquires, engages, and retains customers by connecting out-of-app signals to in-app outcomes and enabling faster, more confident decision-making across the organization.
In this role, you will:
* Design and maintain scalable data models, pipelines, and reporting tools that enable accurate and timely marketing performance measurement across multiple customer engagement channels (e.g., email, push, X-site, WhatsApp, paid media).
* Lead the design, execution, and analysis of A/B tests to evaluate marketing strategies, targeting logic, and content variations—ensuring statistical rigor and actionable insights.
* Deliver deep customer insights by analyzing behavioral data and engagement patterns, helping stakeholder and partner teams better understand customer needs, preferences, and responses to messaging.
* Develop dashboards and self-service tools to enable marketers, product managers, and other stakeholders to explore data, monitor performance, and make informed decisions.
* Collaborate closely with cross-functional teams—including Data Scientists, Engineers, Product Managers, and Marketing Managers—to define metrics, surface insights, and influence strategy through data.
* Communicate findings clearly to both technical and non-technical stakeholders, using data storytelling to highlight opportunities, surface risks, and drive alignment on next steps.
* Champion data accuracy, consistency, and experimentation best practices to raise the overall bar for measurement and insight generation in Prime Video marketing.
Basic Qualifications
- 3+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL etc. 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
- 3+ years of in the job offered or a related occupation experience
- 1+ years of using SQL, ETL (Extract, Transform, Load), or Oracle 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 with data modeling, warehousing and building ETL pipelines
- Experience in Statistical Analysis packages such as R, SAS and Matlab
- Experience using SQL to pull data from a database or data warehouse and scripting experience (Python) to process data for modeling
Preferred Qualifications
- Experience with AWS solutions such as EC2, DynamoDB, S3, and Redshift
- Experience in data mining, ETL, etc. and using databases in a business environment with large-scale, complex datasets
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 - 99,500.00 - 160,000.00 USD annually