Role at a glance
- Salary
- $151.2K – $204.6K/yr
- Location
- Seattle, Washington, United States
- Work arrangement
- On-site
- Employment
- Full-time
- Experience
- 5+ years of systems development engineering, software engineering, or data engineering
- Education
- Bachelor's degree in Computer Science, Engineering, a related field, or equivalent experience
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Role Summary
The System Development Engineer will build and own an executive decision intelligence platform for senior leaders across Amazon's global data center fleet. The platform combines operational data and analytical outputs into structured decisions with context, projected outcomes, recommended actions, visualizations, and automated briefings.
What You'll Do
- Design and build the end-to-end decision intelligence platform and its system architecture
- Build metric decomposition pipelines and implement trend computation, projected outcomes, scenario comparison, and threshold-based alerting
- Ingest and normalize data from multiple upstream operational systems and build ETL pipelines with freshness SLAs, data quality checks,...
- Implement caching, pre-computation, and materialized views for executive dashboard response times
- Integrate science-team outputs and build APIs and serving layers for the web portal and automated report generation
- Build interactive executive dashboards with fleet-wide views, multi-level drill-down, scenario comparison, and automated metric commentary
Generated from the employer's posting. Verify important details before applying.
View full postingQualifications
Required
- Bachelor's degree in Computer Science, Engineering, a related field, or equivalent experience
- 5+ years of systems development engineering, software engineering, or data engineering
- 3+ years building data pipelines, ETL systems, or analytics infrastructure (Python, SQL, Spark, or equivalent)
- 3+ years working with cloud services (AWS preferred: Lambda, DynamoDB/RDS, S3, Redshift/Athena, Step Functions, ECS)
- Experience building and operating production data platforms serving analytical outputs to Experience with at least one web/dashboard framework (Streamlit, FastAPI, Flask, or equivalent)
- Experience designing data models for multi-level aggregation and time-series data
Preferred
- Experience with distributed systems at scale
- Experience building decision support systems or intelligence platforms that serve executive/leadership users
- Experience integrating ML model outputs into production systems (model serving, feature stores, prediction APIs)
- Familiarity with automated report or document generation (templated briefs, PDF/HTML generation)
- Experience with data visualization libraries (Plotly, D3, Altair) or BI tools (QuickSight, Tableau)
- Experience building systems with time-series computation (rolling averages, trend detection, WoW comparison)
- Background in infrastructure operations, capacity planning, or supply chain environments
- Experience with LLM integration for text generation or summarization (prompt engineering, API integration)
Original job description
Content provided by the employer
Original job description
Content provided by the employer
This is a systems engineering role. You will build the platform infrastructure — data pipelines, aggregation engines, decision-framing logic, APIs, visualization layers, and automated briefing systems — that turns raw operational data into structured executive decisions. Where analytical models exist, you will integrate and serve them; your primary focus is building reliable, scalable, well-architected production systems that deliver the right decisions to the right leaders at the right time.
Key job responsibilities
### Build & Own the Decision Intelligence Platform
- Design and build the end-to-end platform
- Own the system architecture that surfaces structured decisions to executives
- Build metric decomposition pipelines
- Implement trend computation, projected outcomes, scenario comparison, and threshold-based alerting at multiple aggregation levels
### Data Pipeline & Platform Infrastructure
- Ingest and normalize data from multiple upstream operational systems
- Build robust ETL pipelines with defined freshness SLAs, data quality checks, and observability
- Implement caching, pre-computation, and materialized views for sub-second executive dashboard response times
### Integration & Serving
- Integrate outputs from science teams into the platform as first-class data sources
- Build the serving layer that presents analytical outputs alongside operational metrics in a unified executive experience
- Implement automated narrative generation (template-based or LLM-assisted) that produces metric commentary for executive reviews
- Design APIs that support both the web portal and automated report generation
### Web Application & Visualization
- Build interactive executive dashboards with fleet-wide views, multi-level drill-down, and scenario comparison
- Implement data visualizations optimized for non-technical senior leaders (clarity over complexity)
- Design the portal to support multiple view modes: summary cards, trend charts, tabular comparisons, commentary threads
Basic Qualifications
- Bachelor's degree in Computer Science, Engineering, a related field, or equivalent experience- 5+ years of systems development engineering, software engineering, or data engineering
- 3+ years building data pipelines, ETL systems, or analytics infrastructure (Python, SQL, Spark, or equivalent)
- 3+ years working with cloud services (AWS preferred: Lambda, DynamoDB/RDS, S3, Redshift/Athena, Step Functions, ECS)
- Experience building and operating production data platforms serving analytical outputs to Experience with at least one web/dashboard framework (Streamlit, FastAPI, Flask, or equivalent)
- Experience designing data models for multi-level aggregation and time-series data
Preferred Qualifications
- Experience with distributed systems at scale- Experience building decision support systems or intelligence platforms that serve executive/leadership users
- Experience integrating ML model outputs into production systems (model serving, feature stores, prediction APIs)
- Familiarity with automated report or document generation (templated briefs, PDF/HTML generation)
- Experience with data visualization libraries (Plotly, D3, Altair) or BI tools (QuickSight, Tableau)
- Experience building systems with time-series computation (rolling averages, trend detection, WoW comparison)
- Background in infrastructure operations, capacity planning, or supply chain environments
- Experience with LLM integration for text generation or summarization (prompt engineering, API integration)
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.
USA, WA, Seattle - 151,200.00 - 204,600.00 USD annually
About the company
amazon
Large Enterprise
Amazon is a global leader in e-commerce and cloud computing, founded in 1994 by Jeff Bezos. Initially starting as an online bookstore, it has since expanded its offerings to include a vast range of products and services, including electronics, fashion, and digital content. With Amazon Web Services (AWS), the company also provides powerful cloud solutions to businesses around the world. Known for its innovation, customer-centric approach, and commitment to operational efficiency, Amazon continues to shape the future of retail and technology, consistently seeking new ways to enhance customer experiences.
Amazon is a global leader in e-commerce and cloud computing, founded in 1994 by Jeff Bezos. Initially starting as an online bookstore, it has since expanded its offerings to include a vast range of products and services, including electronics, fashion, and digital content. With Amazon Web Services (AWS), the company also provides powerful cloud solutions to businesses around the world. Known for its innovation, customer-centric approach, and commitment to operational efficiency, Amazon continues to shape the future of retail and technology, consistently seeking new ways to enhance customer experiences.