Data Engineer, PXTCS — Build Scalable ML Pipelines

Amazon.com Services LLC; Kent (WA); On-site; USD 120,000 - 180,000; Full time

Job summary

Amazon.com Services LLC's PXTCS team uses economics, behavioral science, statistics, machine learning, and Generative AI to improve Amazonians' lives and value at work. As a Data Engineer on PXTCS, you'll build scalable data pipelines, productionize models, and partner with economists, data scientists, and software engineers to deliver insights across benefits, compensation, and workforce programs.

This role focuses on turning cutting-edge ML and AI into reliable production systems that scale to

Qualifications

• 3+ years of data engineering experience.
• Experience with data modeling, warehousing and building ETL pipelines.
• Familiarity with AWS technologies (Redshift, S3, Glue, EMR, Kinesis, Lambda).
• Experience with non-relational databases / data stores.
• Knowledge of software development lifecycle and best practices.

Responsibilities

• Design and maintain scalable data pipelines using native AWS services.
• Develop APIs and data serving layers for model productionization.
• Build feature extraction and processing frameworks for diverse data types.
• Ensure data quality, validation checks, and evolving schemas.
• Collaborate with economists, data scientists, and software engineers on production-ready solutions.

Skills

Data engineering

Python

Java

Scala

NodeJS

ETL pipelines

Tools

AWS Redshift

AWS S3

AWS Glue

AWS EMR

AWS Kinesis

AWS Lambda

IAM

Job description

Amazon.com Services LLC's PXTCS team uses economics, behavioral science, statistics, machine learning, and Generative AI to improve Amazonians' lives and value at work. As a Data Engineer on PXTCS, you'll build scalable data pipelines, productionize models, and partner with economists, data scientists, and software engineers to deliver insights across benefits, compensation, and workforce programs.

This role focuses on turning cutting-edge ML and AI into reliable production systems that scale to