Data Engineer, AWS Pipelines & Production Analytics

Amazon

Bellevue (WA)

On-site

USD 132,000 - 179,000

Full time

2 days ago
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Benefits offered by this job

Health insurance
401(k) matching
Paid time off
Parental leave

Job summary

Amazon.com Services LLC is seeking a Data Engineer to join the PXT Central Science team in Bellevue, WA. The role focuses on owning and accelerating analytics for employee insights, building scalable data environments, and producing production-ready data solutions for economists and data scientists.

You will design end-to-end data pipelines, contribute to feature extraction, and ensure data quality across diverse data types while collaborating with engineers and researchers to translate

Qualifications

  • 3+ years of data engineering experience.
  • Experience with AWS data services (Glue, EMR, Lambda, S3, Redshift, Kinesis).
  • Experience with data modeling, warehousing and ETL pipelines.
  • Experience with non-relational data stores.

Responsibilities

  • Design and maintain scalable data pipelines on native AWS services; monitor and optimize data workflows.
  • Develop and maintain APIs and data serving layers for model productionization.
  • Build feature extraction frameworks and data quality checks; support evolving schemas.
  • Collaborate with economists, data scientists, and software engineers to translate requirements into production solutions.
  • Maintain layered data systems and automated reporting across multiple AWS accounts.

Skills

Data pipelines
AWS data services
ETL development
Programming languages
Data modeling
API development
Data quality checks

Tools

AWS Glue
EMR
S3
Redshift
Kinesis
Lambda
IAM

Job description

Amazon.com Services LLC is seeking a Data Engineer to join the PXT Central Science team in Bellevue, WA. The role focuses on owning and accelerating analytics for employee insights, building scalable data environments, and producing production-ready data solutions for economists and data scientists.

You will design end-to-end data pipelines, contribute to feature extraction, and ensure data quality across diverse data types while collaborating with engineers and researchers to translate

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