Data Engineer - Production ML Pipelines for People Ops

Amazon; Arlington (VA); On-site; USD 132,000 - 179,000; Full time

Benefits offered by this job

Health insurance

401(k) matching

Paid time off

Parental leave

Workplace accommodations

Job summary

Amazon’s PXTCS Data Engineering role focuses on turning ML and Generative AI models into reliable, scalable production systems. You will craft scalable data pipelines, productionize APIs, and collaborate with economists, data scientists, and engineers to translate insights into actionable solutions.

The role emphasizes building robust data architectures, ensuring data quality, and operating across multiple AWS accounts with security best practices, contributing to impactful decisions affecting

Qualifications

• Experience in data engineering across full software lifecycle.
• Proficient in Python/Java/Scala or NodeJS.
• Strong ETL design, data modeling and warehousing.
• Hands-on with AWS data services (Glue, EMR, Lambda, Redshift).
• Experience with non-relational databases and data stores.

Responsibilities

• Design and maintain scalable data pipelines using native AWS services.
• Develop APIs and data serving layers to productionize models.
• Build feature extraction and processing frameworks for diverse data types.
• Collaborate with economists, data scientists, and engineers to translate requirements into production solutions.
• Maintain layered data systems and automated reporting across AWS accounts.

Skills

Full software dev life cycle

Python/Java/Scala

ETL pipelines

AWS data services

Data modeling

Tools

AWS Glue

EMR

Lambda

Redshift

S3

Kinesis

IAM

Job description

Amazon’s PXTCS Data Engineering role focuses on turning ML and Generative AI models into reliable, scalable production systems. You will craft scalable data pipelines, productionize APIs, and collaborate with economists, data scientists, and engineers to translate insights into actionable solutions.

The role emphasizes building robust data architectures, ensuring data quality, and operating across multiple AWS accounts with security best practices, contributing to impactful decisions affecting