Data Engineer II: Sales Data Services (AWS/ETL)

Amazon Inc.; Seattle (WA); On-site; USD 132,000 - 179,000; Full time

Job summary

Amazon Inc. in Seattle, WA is seeking a Data Engineer II to join Sales Data Services. You will design data warehouse and data lake infrastructure using AWS, develop ETL/ELT pipelines, and enable self-serve analytics for internal customers.

You will mentor engineers and collaborate across BI, data science, and product teams. The role emphasizes scalable, robust data architectures, exposure to large datasets, and building analytics-ready data models leveraging Redshift, S3, Glue, and other AWS

Qualifications

• 3+ years of data engineering experience.
• 1+ years building ETL/ELT pipelines for BI analytics.
• 1+ years building and operating OLAP data structures.
• 1+ years data modeling for analytics.
• 1+ years SQL experience in large datasets.
• 1+ years Oracle experience.
• Bachelor's degree or foreign equivalent in CS/Engineering/IS/Math.
• Experience with data warehousing and ETL pipelines.

Responsibilities

• Design, implement, and support data warehouse / data lake infra using AWS stack, Python, Redshift.
• Develop and manage ETLs to source data from data lakes and create unified data model.
• Enable self-serve analytics and ad-hoc reporting for internal customers.
• Develop understanding of data sources and appropriate data usage for problems.
• Manage multiple requests, prioritize, and collaborate across teams.
• Mentor engineers and contribute to team culture.

Skills

Data engineering

ETL/ELT

OLAP

Data modeling

SQL

Oracle

Education

Bachelor's degree in Computer Science / Engineering / Information Systems / Mathematics

Tools

AWS Redshift

S3

AWS Glue

EMR

Kinesis

Lambda

IAM roles

Job description

Amazon Inc. in Seattle, WA is seeking a Data Engineer II to join Sales Data Services. You will design data warehouse and data lake infrastructure using AWS, develop ETL/ELT pipelines, and enable self-serve analytics for internal customers.

You will mentor engineers and collaborate across BI, data science, and product teams. The role emphasizes scalable, robust data architectures, exposure to large datasets, and building analytics-ready data models leveraging Redshift, S3, Glue, and other AWS