Data Engineer II, NAST CX Tech
Amazon - Bellevue, Washington, USA
Posted May 8, 2026
Benefits
- Parental leave
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- Non-birth-parent leave
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- Family-building benefits
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- Fertility benefits: Not verified
- Adoption assistance: Not verified
- Surrogacy assistance: Not verified
- Mental health support
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- Relocation assistance
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- Childcare support
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- Learning budget
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- Salary
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- 401(k) match
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Schedule
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- Weekend work
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Application
- Cover letter
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- Assessment
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- Deadline
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Where they hire
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About this role
Data Engineer II, NAST CX Tech Bellevue, Washington, USA The NAST Customer Experience (CX) Tech team is looking for a Data Engineer II to build and scale the data infrastructure that powers operational intelligence for Amazon's North American Surface Transportation (NAST) Linehaul network. You will design data pipelines, build analytical platforms, and develop AI-powered tools that operations leaders use daily to monitor performance, identify root causes, and drive decisions across a network that moves millions of packages every day. This is a high-impact role where your work directly shapes how leadership understands and acts on metrics like Delivery Estimate Accuracy (DEA), Process Failure Rate (Xenith), and trailer inspection quality (VTI). You will work across the full data stack from ingestion and transformation to AI tools and front-end delivery using AWS-native services and modern data tools and technologies. Key job responsibilities You will design and maintain scalable data pipelines that ingest and transform operational metrics from sources like Andes, Datanet, and Redshift using SparkSQL, Cradle, and AWS services (Glue, Lambda, S3, Step Functions). You will build and extend AI-powered analytical applications using AWS Bedrock, DynamoDB, and Python that generate automated performance summaries and insights. You will own data modeling for new metric onboarding, drive migration of legacy SQL workloads to modern platforms, manage infrastructure-as-code with AWS CDK across gamma and production environments, and implement monitoring, alerting, and validation frameworks to ensure pipeline reliability. You will collaborate with operations leaders and data scientists to translate business needs into data solutions that scale.
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