Data Engineer II, Creator Services

Amazon's Creator Services leads creator programs spanning media, commerce, and culture. The company is seeking a Data Engineer II to build scalable data platforms, production-grade pipelines, curated datasets, and internal tools that support AI initiatives, self-service analytics, and creator monetization.

Responsibilities

• Design, build, and maintain production-grade ETL/ELT pipelines that process data at scale with high reliability and performance
• Architect and curate data models, warehouses, and dimensional schemas that serve as the foundation for self-service analytics and AI initiatives
• Drive end-to-end technical ownership of data platform components — from system design and architecture reviews to deployment, monitoring, and incident response
• Leverage AWS services — including Redshift, S3, Glue, Lambda, ECS, DynamoDB, and Bedrock — to build scalable and cost-efficient data platforms
• Partner with BI engineers, program managers, and business stakeholders to translate data needs into technical solutions, while advocating for data engineering best practices across the team

Preferred

• Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions
• Experience with non-relational databases / data stores (object storage, document or key-value stores, graph databases, column-family databases)
• Strong foundation in data governance, access controls, and compliance standards (e.g., IAM least-privilege, data classification, security certifications)
• Demonstrated ability to provide technical leadership and advocating for data engineering best practices across cross-functional teams
• Skilled at designing and building internal tools, APIs, or software applications that serve data products or automate business processes
• Experience applying AI/ML technologies (e.g., large language models, generative AI, or predictive modeling) to data engineering or automation use cases
• Amazon Redshift
• Amazon S3
• AWS Glue
• Amazon EMR
• Amazon Kinesis
• Amazon Kinesis Data Firehose
• AWS Lambda
• AWS IAM
• IAM Roles
• Permissions
• Non-Relational Databases
• Object Storage
• Document Stores
• Key-Value Stores
• Graph Databases
• Column-Family Databases
• Data Governance
• Access Controls
• Compliance Standards
• Least-Privilege Access
• Data Classification
• Security Certifications
• Data Engineering Best Practices
• Internal Tool Development
• API Design
• Software Application Development
• Data Products
• Business Process Automation
• AI/ML Applications
• Large Language Models
• Generative AI
• Predictive Modeling
• Technical Leadership
• Cross-Functional Collaboration
• Advocacy

Benefits

• Sign-on payments
• Restricted stock units (RSUs)
• Health insurance, including medical, dental, vision, prescription, Basic Life & AD&D insurance, and an option for Supplemental life plans
• Employee Assistance Program (EAP)
• Mental Health Support
• Medical Advice Line
• Flexible Spending Accounts
• Adoption and Surrogacy Reimbursement coverage
• 401(k) matching
• Paid time off
• Parental leave

Company

• Online retail and cloud computing services
• Seattle, Washington, USA
• https://amazon.com/
• Founded in 1994
• 10001+ employees

Qualifications

• 3+ years of data engineering experience
• Bachelor's degree
• 3+ years of data warehouse technical architectures, data modeling, infrastructure components, ETL/ ELT and reporting/analytic tools and environments, data structures and hands-on SQL coding experience
• Experience with database, data warehouse or data lake solutions
• Experience with AWS technologies like Redshift, S3, AWS Glue, EMR, Kinesis, FireHose, Lambda, and IAM roles and permissions
• Experience with non-relational databases / data stores (object storage, document or key-value stores, graph databases, column-family databases)
• Strong foundation in data governance, access controls, and compliance standards (e.g., IAM least-privilege, data classification, security certifications)
• Demonstrated ability to provide technical leadership and advocating for data engineering best practices across cross-functional teams
• Skilled at designing and building internal tools, APIs, or software applications that serve data products or automate business processes
• Experience applying AI/ML technologies (e.g., large language models, generative AI, or predictive modeling) to data engineering or automation use cases

Required skills

• Data Engineering, SQL, ETL/ELT Pipelines, Data Warehousing, Data Modeling, AWS Redshift, Amazon S3, AWS Glue, AWS Lambda, Amazon DynamoDB, AWS IAM, Non-Relational Databases, Data Governance, API Development, AI/ML

Experience

• 3+ years