Data Engineer, Amazon Prime Video Product Analytics
About The Position
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.
Requirements
- 3+ years of data engineering experience
- Experience with data modeling, warehousing and building ETL pipelines
- 3+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL etc. experience
- Experience with SQL
Nice To Haves
- Experience with non-relational databases / data stores (object storage, document or key-value stores, graph databases, column-family databases)
- Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions
Responsibilities
- Design, implement, and maintain scalable and reliable data models and ETL pipelines that span the full customer funnel—including the reporting layer for the out-of-app messaging platform and other PV marketing channel infrastructure.
- Build and enhance the AI tooling and analytics products to enable self-serve and improved efficiency.
- Partner with engineering and dependency teams to define data contracts, ensure upstream data reliability, and proactively manage communication and change coordination for data schema updates.
- Collaborate with Business Intelligence Engineers and Data Scientists to deliver clean, structured data for dashboards, reporting, experimentation, full-funnel attribution, and ML use cases.
- Monitor pipeline health, resolve job and cluster issues, and improve automation, testing, and observability to increase system resilience.
- Champion data engineering best practices across the team—including documentation, version control, peer reviews, and operational excellence.
Benefits
- 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
- parental leave
- sign-on payments
- restricted stock units (RSUs)
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Education Level
No Education Listed
