Data Engineer II, AAE
Amazon - Bellevue, Washington, USA
Posted May 18, 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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- Verification
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- Salary
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- 401(k) match
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Schedule
- Shift type
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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
State eligibility is not yet verified.
About this role
Data Engineer II, AAE Bellevue, Washington, USA AWS AI Services is one of the largest and fastest-growing business units within AWS, powering services like Amazon Bedrock, AgentCore, QuickSight, Q Business, Kendra, and Kiro. Our Data Engineering team builds the intelligence infrastructure that makes this portfolio measurable - from revenue attribution and launch telemetry to agent-generated business reviews that serve VP-level leadership weekly. We are looking for an experienced, self-driven Data Engineer to join a team that operates at the intersection of data engineering and agentic AI. In this role, you won't just build pipelines - you'll design data platforms that power AI agents, build automated reporting systems that replace manual processes, and create the data foundations that prove business impact across a multi-billion dollar service portfolio. You'll work with modern AWS-native data stacks (Glue, Redshift, Athena, QuickSight, Bedrock, SageMaker), build event-driven architectures with CDK, and contribute to agentic workflows that generate executive-level insights autonomously. You should be comfortable operating in ambiguity, designing data models from scratch for new services, and making architectural trade-off decisions that scale. This is a high-visibility role. Your work will directly inform decisions made by VPs, GMs, and the CFO's office - from revenue unification mandates to enterprise deal velocity to AI adoption measurement. Key job responsibilities Design and build end-to-end data platforms for new AWS AI services - defining schemas, data models, ETL pipelines, and analytics infrastructure where none exists today Build and maintain production ETL/ELT pipelines using AWS Glue, Airflow, Spark, and Python to
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