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Amazon.com Services LLC

Data Engineer

Amazon.com Services LLC
Seattle, WA $132k - $179k/yr Full time Posted 29d ago
Analytics Artificial Intelligence AWS Big Data Data Analytics Data Architecture Data Engineer Data Integration Data Pipeline Data Platform Data Processing Data Warehouse Database ETL Firehose SQL
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Job Description

Join Amazon.com Services LLC as a Data Engineer II on the Prime Video Product Analytics (PVPA) team. This onsite role in Seattle, WA offers a competitive salary range of USD 132,100 to 178,800 per year, along with a comprehensive benefits package that includes health insurance, 401(k) matching, paid time off, parental leave, sign-on payments, and RSUs.

The role centers on building and maintaining data infrastructure and pipelines that power out-of-app analytics, full-funnel customer journey insights, experimentation, and machine learning use cases for personalization and measurement.

Responsibilities

  • Build and maintain the data infrastructure that powers Prime Video's out-of-app and full-funnel analytics.
  • Own critical datasets and pipelines that support analytics, experimentation, and machine learning use cases, enabling smarter targeting, personalization, and measurement.
  • Design, implement, and maintain scalable and reliable data models and ETL pipelines that span the full customer funnel, including the reporting layer for the out-of-app messaging platform and PV marketing channel infrastructure.
  • Build and enhance the AI tooling and analytics products to enable self-serve and improved efficiency.
  • Partner with engineering and dependency teams to define data contracts, ensure upstream data reliability, and proactively manage communication and change coordination for data schema updates.
  • Collaborate with Business Intelligence Engineers and Data Scientists to deliver clean, structured data for dashboards, reporting, experimentation, full-funnel attribution, and ML use cases.
  • Monitor pipeline health, resolve job and cluster issues, and improve automation, testing, and observability to increase system resilience.
  • Champion data engineering best practices across the team including documentation, version control, peer reviews, and operational excellence.

Requirements

  • 3+ years of data engineering experience
  • Experience with data modeling, warehousing and building ETL pipelines
  • 3+ years of analyzing and interpreting data with Redshift, Oracle, NoSQL etc. experience
  • Experience with SQL

Technologies

  • Redshift
  • Oracle
  • NoSQL
  • S3
  • AWS Glue
  • EMR
  • Kinesis
  • FireHose
  • Lambda
  • IAM

Benefits

  • Health insurance
  • 401(k) matching
  • Paid time off
  • Parental leave
  • Sign-on payments
  • RSUs (restricted stock units)

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