Data Engineer II: Prime Video Analytics & Attribution

Prime Video & Amazon MGM Studios; Seattle (WA); On-site; USD 132,000 - 179,000; Full time

Benefits offered by this job

Health insurance

401(k) matching

Paid time off

Parental leave

RSUs

Job summary

Amazon.com Services LLC is seeking a Data Engineer II for the Prime Video Product Analytics (PVPA) team in Seattle. You will design and maintain data pipelines powering out-of-app and full-funnel analytics, enabling smarter targeting, personalization, and measurement across marketing touchpoints.

You will own key datasets, partner with engineers and data scientists, and focus on data reliability, experimentation support, and scalable data models to drive customer insights and product decisions.

Qualifications

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

Responsibilities

• Design, implement, and maintain scalable data models and ETL pipelines for full funnel analytics.
• Build and enhance AI tooling and analytics products for self-serve insights.
• Collaborate to define data contracts and ensure data quality and reliability.
• Deliver clean, structured data for dashboards, reporting, and ML use cases.
• Monitor pipeline health and improve automation and observability.
• Champion data engineering best practices across the team.

Skills

Data engineering

Data modeling

SQL

Redshift

Oracle

NoSQL

Tools

AWS Redshift

S3

AWS Glue

EMR

Kinesis

Firehose

Lambda

IAM

Job description

Amazon.com Services LLC is seeking a Data Engineer II for the Prime Video Product Analytics (PVPA) team in Seattle. You will design and maintain data pipelines powering out-of-app and full-funnel analytics, enabling smarter targeting, personalization, and measurement across marketing touchpoints.

You will own key datasets, partner with engineers and data scientists, and focus on data reliability, experimentation support, and scalable data models to drive customer insights and product decisions.