Data Platform Engineer for Payments Analytics

JobCubby; Seattle (WA); On-site; USD 130,000 - 180,000; Full time

Job summary

Amazon is seeking a Data Engineer to design, build, and scale data pipelines for Digital Payments & Emerging Markets in Seattle. You’ll work with data modeling, warehousing, and ETL across the Data Lake and EMR/Spark environments to support product analytics, fraud detection, and regional payment methods.

You will collaborate with Product, Science, BI, and ML teams to expand events, datasets, and reports, leveraging AWS Redshift, S3, EMR, and Glue-like workflows.

Qualifications

• Experience as a Data Engineer or in a similar role
• Experience with data modeling, warehousing and building ETL pipelines
• Experience with SQL
• Experience in at least one modern scripting or programming language, such as Python, Java, Scala, or NodeJS
• Experience mentoring team members on best practices

Responsibilities

• Big data design, analysis, data modeling, and the development, deployment, and operation of large-scale data pipelines.
• Manage the data exchange store (Data Lake) and the EMR/Spark processing layer, using Airflow as the orchestrator.
• Build and protect a robust self-service core data experience for internal customers across key business domains (e.g., payment conversion, fraud, and regional payment methods).
• Partner with Product, Marketing, BI, and ML teams to deliver new events, pipelines, datasets, models, and reporting.
• Work hands-on with AWS technologies including Redshift, S3, EMR, EC2, DynamoDB, Kinesis Firehose, and Lambda.

Skills

Data modeling

Data warehousing

ETL pipelines

SQL

Python

Java/Scala/NodeJS

Mentoring

Tools

AWS Redshift

AWS S3

EMR

DynamoDB

Kinesis Firehose

Lambda

Job description

Amazon is seeking a Data Engineer to design, build, and scale data pipelines for Digital Payments & Emerging Markets in Seattle. You’ll work with data modeling, warehousing, and ETL across the Data Lake and EMR/Spark environments to support product analytics, fraud detection, and regional payment methods.

You will collaborate with Product, Science, BI, and ML teams to expand events, datasets, and reports, leveraging AWS Redshift, S3, EMR, and Glue-like workflows.