Data Engineer II, Creator Services — Scale AI-Driven Data

Amazon Game Studios; Culver City (CA); On-site; USD 132,000 - 179,000; Full time

Benefits offered by this job

Health insurance

RSUs

401(k) matching

Paid time off

Job summary

Amazon is seeking a Data Engineer to join the Creator Services data and tech team in Culver City, CA. You will design and operate production-grade ETL/ELT pipelines, curate data warehouses and dimensional models, and own data platform components end to end to support analytics and AI initiatives.

You will collaborate with BI engineers and business stakeholders, leverage AWS tools to scale data platforms, and build internal tools that automate workflows while maintaining governance and security.

Qualifications

• 3+ years of data engineering experience.
• Bachelor's degree in a relevant field.
• 3+ years of data warehouse architectures, data modeling, ETL/ELT and analytics tools.
• Experience with database, data warehouse or data lake solutions.

Responsibilities

• Design, build, and maintain production-grade ETL/ELT pipelines for large-scale data processing.
• Architect and curate data models, warehouses, and dimensional schemas for self-service analytics and AI initiatives.
• Own data platform components from design to deployment, monitoring, and incident response.
• Leverage AWS services to build scalable, cost-efficient data platforms.
• Partner with BI engineers and stakeholders to translate data needs into technical solutions.

Skills

Data pipelines

SQL

AWS

Data modeling

ETL/ELT

Education

Bachelor's degree

Tools

AWS Redshift

AWS S3

AWS Glue

AWS Lambda

IAM

DynamoDB

Job description

Amazon is seeking a Data Engineer to join the Creator Services data and tech team in Culver City, CA. You will design and operate production-grade ETL/ELT pipelines, curate data warehouses and dimensional models, and own data platform components end to end to support analytics and AI initiatives.

You will collaborate with BI engineers and business stakeholders, leverage AWS tools to scale data platforms, and build internal tools that automate workflows while maintaining governance and security.