Senior Data Engineer — AWS Pipelines & AI-Ready Analytics

Amazon.com Services LLC; Seattle (WA); On-site; USD 155,000 - 209,000; Full time

Benefits offered by this job

Sign-on payments

RSUs

Health insurance

401(k) matching

Paid time off

Parental leave

Job summary

Amazon.com Services LLC in Seattle, WA, is hiring a Senior Data Engineer to architect and evolve AWS data infrastructure for Paragon. You will design scalable data pipelines, model data, and support reporting, analytics, and ML initiatives.

The role combines hands-on engineering with technical leadership, mentoring teammates, and shaping data governance across global teams. A strong background in data warehousing, ETL, SQL, and AWS is essential.

Qualifications

• 5+ years of data engineering experience.
• Experience with data modeling, warehousing, and ETL pipelines.
• Experience with SQL.
• Experience with Python, Java, Scala, or NodeJS.
• Experience mentoring team members.

Responsibilities

• Design and operate scalable AWS data pipelines and infrastructure for reporting, analytics, and ML.
• Define logical data models and architectures to support worldwide growth.
• Lead data architecture reviews with senior stakeholders across functions.
• Establish and maintain data engineering standards for modeling, lineage, governance, and reliability.
• Mentor and coach engineers to strengthen team capability.

Skills

Data modeling

Warehousing

ETL pipelines

SQL

Python

Java/Scala/NodeJS

Mentoring

Education

Master’s degree in CS/Engineering/Analytics/Math/Statistics/IT

Tools

AWS

SQL

Python

Java

Scala

Hadoop

Hive

Spark

EMR

Job description

Amazon.com Services LLC in Seattle, WA, is hiring a Senior Data Engineer to architect and evolve AWS data infrastructure for Paragon. You will design scalable data pipelines, model data, and support reporting, analytics, and ML initiatives.

The role combines hands-on engineering with technical leadership, mentoring teammates, and shaping data governance across global teams. A strong background in data warehousing, ETL, SQL, and AWS is essential.