Data Engineer, Compensation, CPSA
Amazon - Seattle, 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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- 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
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About this role
Data Engineer, Compensation, CPSA Seattle, Washington, USA Amazon Compensation Data team is looking for Data Engineer (DE) to join our team for modernizing data warehouses serving business intelligence, data science and AI customers globally. Your role will involve designing, implementing, and supporting scalable solutions for metadata management, data pipeline orchestration, ETL, data modelling and data visualization with the tools available from AWS - including Sage Maker Unified Studio, Redshift, Glue, S3, IAM, Cloudwatch, and Apache Airflow. As DE you will be managing data infrastructure ,building automated CDK based solution. You will work with stakeholders to gather requirements for data logging,storing,transforming and reporting. The ideal candidate will be passionate about working with big data sets and have the expertise to utilize these datasets to answer business questions and drive for best-in-class analytics, dashboard design and new innovative approaches.The ideal candidate will be entrepreneurial and innovative, thriving on solving challenging, ambiguous problems Key job responsibilities Lead the modernization of one of compensation data warehouses serving customers globally. As a Data Engineering, you'll architect scalable data infrastructure solutions, partner with business, product, and data science teams to deliver analytics and insights that drive day-to-day decision-making across the organization. A day in the life What you'll do: Build end-to-end systems from ideation, experimentation through production deployment Design and implement AI agents that automate complex decisions Work directly with customer teams to identify automation opportunities and measure impact Own the full project lifecycle: data pipelines, deployment, and monitoring Basic Qualifications: - 5+ years of data
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