Data Engineer, Amazon Prime Video Product Analytics

Amazon; Seattle (WA); On-site; USD 132,100 - 178,800; Full time

Benefits offered by this job

Health insurance

401(k) matching

Paid time off

Parental leave

Job summary

Amazon in Seattle is looking for a Data Engineer II to join the Prime Video Product Analytics team. You will design and maintain data models and ETL pipelines to enhance customer engagement and journey analytics.

The role requires over 3 years of data engineering experience, proficiency in SQL, and familiarity with AWS technologies like Redshift and S3. The position offers competitive salary and comprehensive benefits.

Qualifications

• 3+ years of data engineering experience.
• Experience with data modeling, warehousing and building ETL pipelines.
• Experience with SQL, Redshift, Oracle, and NoSQL.

Responsibilities

• Design and maintain scalable data models and ETL pipelines.
• Build AI tooling and analytics products for self-service.
• Monitor pipeline health and improve system resilience.

Skills

Data engineering

Data modeling

ETL pipelines

SQL

Data analysis

Tools

Redshift

AWS Glue

S3

Oracle

NoSQL

Job description

Description

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 Data Engineer II to join the PVPA team. In this role, you will be responsible for building and maintaining the data infrastructure that powers Prime Video’s out‑of‑app and full‑funnel customer journey analytics. You will own critical datasets and pipelines that directly support analytics, experimentation, and machine learning use cases, enabling smarter targeting, personalization, and measurement.

As a Data Engineer on the PVPA team, you will:

• 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.

Basic Qualifications

• 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

Preferred Qualifications

• 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

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 - 132,100.00 - 178,800.00 USD annually