Data Engineer, PXT Central Science
Amazon - Seattle, Washington, USA
Posted May 9, 2026
Benefits
- Parental leave
- 6 weeks From the posting source checked Jun 20, 2026
- Non-birth-parent leave
- 6 weeks From the posting source checked Jun 20, 2026
- Family-building benefits
- Mental health support
- Offered From the posting source checked Jun 20, 2026
- Relocation assistance
- Not verified
- Childcare support
- Offered From the posting source checked Jun 20, 2026
- Learning budget
- Not verified
- Verification
- Source-linked checked Jun 7, 2026
- Salary
- $132K-$179K From the posting source checked Jun 20, 2026
- 401(k) match
- Reported from DOL Form 5500 industry filing (not employer-specific)
Was this benefit information wrong? Tell us.
Market context
- U.S. role benchmark (BLS OEWS)
- $111,944 U.S. median for this role
- Projected growth (BLS Employment Projections)
- +13.7% - Much faster than average
39% above the BLS role benchmark for data and ml aggregate.
Matched to SOC 15-1252 - Data and ML aggregate by role bucket.
Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.
Role
Schedule
- Shift type
- Not verified
- Weekend work
- Not verified
Company
Application
- Cover letter
- Not verified
- Assessment
- Not verified
- Deadline
- Not stated
Where they hire
State eligibility is not yet verified.
About this role
Data Engineer, PXT Central Science Seattle, Washington, USA The PXT Central Science team is looking for a Data Engineer. This individual will join a team of economists and scientists to own and accelerate science and analytics in our rapid employee intelligence workstream. This suite of models identifies causal factors driving changes in employee sentiment, actions, and business outcomes. Key job responsibilities PXTCS is looking for a data engineer with expertise in complex data environments. You will be responsible for enhancing our existing data architecture to further standardize metrics and definitions, building and testing new features, developing end-to-end data engineering solutions for complex analytical problems, and collaborating with economists, data scientists, and software engineers to translate data into actionable insights. Specific responsibilities include: • Data Pipeline Development: Design and maintain scalable data pipelines using native AWS services (Glue, EMR, Lambda); build monitoring and error handling for data workflows; optimize performance, reliability, and cost efficiency • Model Productionization & API Development: Develop and maintain APIs and data serving layers that productionize science models for downstream consumption; build batch and real-time inference pipelines • Data Integration & Quality: Build scalable feature extraction and processing frameworks for diverse data types; develop robust data quality and validation checks; create flexible schemas supporting evolving requirements • Cross-team Collaboration: Partner with economics, data science, and software engineering teams to translate analytical requirements into production-ready solutions; participate in technical design reviews and architecture discussions • Analytics & Infrastructure: Maintain layered data systems used by economists and scientists; build
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