Data Engineer II, Global Finance Operations Platform

Amazon; Factoria (WA); On-site; USD 132,000 - 179,000; Full time

Benefits offered by this job

Health insurance

RSUs

401(k) matching

Paid time off

Parental leave

Job summary

Amazon.com Services LLC is seeking a data engineer to design and maintain scalable ETL pipelines and data models within its Outbound Transportation analytics platform. You will collaborate with finance and BI teams to deliver trusted datasets and optimize performance at scale.

Responsibilities include working with Python, SQL, Spark, and AWS (S3, Glue, Redshift, EMR, Lambda) to automate data flows and extend item-level cost granularity across regions.

Qualifications

• 3+ years of data engineering experience
• Experience with data modeling, warehousing and building ETL pipelines
• Bachelor's degree
• Experience in at least one modern scripting or programming language (Python, Java, Scala, NodeJS)
• Knowledge of distributed systems as it relates to data storage and computing

Responsibilities

• Design, build, and maintain scalable ETL pipelines and data solutions using Python, SQL, Spark, and AWS services (S3, Glue, Redshift, Airflow, EMR, Lambda)
• Create coherent logical and physical data models that drive the metadata-driven configuration layer
• Collaborate with finance stakeholders, BI Engineers, and partner teams to gather requirements and deliver trusted datasets
• Participate in code reviews, design discussions, and team planning to increase automation and reduce manual error
• Optimize query performance and resource usage across the data platform

Skills

Data engineering

ETL pipelines

Distributed systems

Python/Java/Scala/NodeJS

Education

Bachelor's degree

Tools

AWS

Redshift

S3

Job description

Amazon.com Services LLC is seeking a data engineer to design and maintain scalable ETL pipelines and data models within its Outbound Transportation analytics platform. You will collaborate with finance and BI teams to deliver trusted datasets and optimize performance at scale.

Responsibilities include working with Python, SQL, Spark, and AWS (S3, Glue, Redshift, EMR, Lambda) to automate data flows and extend item-level cost granularity across regions.