Senior Data Engineer, Selling Partner Insights and 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’s Selling Partner Insights and Analytics (SPIA) team is hiring a Senior Data Engineer to architect and evolve AWS data infrastructure for Paragon.

Responsibilities

• Design and operate scalable, cost-effective AWS data pipelines and infrastructure, curating data for reporting, analytics, and machine learning
• Define logical data models and architectures to support worldwide growth by anticipating data access patterns and removing bottlenecks before they affect customers
• Lead data architecture design reviews and collaborate with directors, VPs, and cross-functional partners to align technical direction with business strategy
• Establish and maintain data engineering standards for data modeling, lineage, governance, and operational reliability across systems
• Coach and mentor other data engineers, supporting professional development and strengthening team technical capability

Requirements

• 5+ years of data engineering experience
• Experience with data modeling, warehousing, and building ETL pipelines
• Experience with SQL
• Experience with at least one modern scripting or programming language: Python, Java, Scala, or NodeJS
• Experience mentoring team members on best practices

Technologies

• AWS
• SQL
• Python, Java, Scala, NodeJS
• Hadoop, Hive, Spark, EMR

Preferred Qualifications

• Experience with big data technologies: Hadoop, Hive, Spark, EMR
• Experience operating large data warehouses
• Master’s degree in computer science, engineering, analytics, mathematics, statistics, IT, or equivalent
• Experience building and operating highly available, distributed systems for data extraction, ingestion, and processing of large datasets
• Experience providing technical leadership and mentoring engineers on data engineering best practices
• Experience communicating with business users, technical teams, and senior leadership to collect requirements and explain data modeling decisions and data engineering strategy

Location

• Seattle, WA (onsite)

Compensation

• USD 154,600 - 209,100 per year

Benefits

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

A Day in the Life

• Split time between hands-on engineering and technical leadership
• Review pipeline health dashboards, triage data quality issues, and pair with teammates on complex ETL problems
• Shift into design discussions with partner teams, review architecture proposals, and share data strategy updates with senior leadership
• Evaluate how team data solutions can evolve to support agentic AI workloads, including architectural recommendations that influence the roadmap

About the Team

• SPIA’s mission is to shorten the path from data to insight for 200+ internal customer teams across Selling Partner Support
• Building the data foundation for current analytics needs and AI-powered experiences
• Datasets, models, and pipelines influence decisions that affect millions of customers and sellers every day
• Clear growth path toward team lead responsibilities, engagement with senior leadership, and helping design the transition of the data platform into the agentic AI era