Senior Systems Dev Engineer: Executive Decision Platform

Amazon; Seattle (WA); On-site; USD 151,200 - 204,600; Full time

Job summary

Amazon Data Services, Inc. is seeking a Sr. Systems Development Engineer to design, build, and own a decision intelligence platform for senior leaders across Amazon's global data center fleet.

You will design end-to-end platforms, own system architecture, and implement ETL pipelines, data models, and APIs. The role emphasizes scalable data infrastructure, automated narratives, and executive-friendly visualizations.

Qualifications

• Bachelor's degree in CS, Engineering, a related field, or equivalent experience.
• 5+ years of systems development engineering or related
• 3+ years building data pipelines, ETL systems, or analytics infrastructure (Python, SQL, Spark)
• 3+ years with cloud services (AWS)
• Experience with web/dashboard frameworks (Streamlit, FastAPI, Flask)
• Experience designing data models for multi-level aggregation and time-series data

Responsibilities

• Design and build the end-to-end decision intelligence platform.
• Own the system architecture that surfaces structured decisions to executives.
• Build metric decomposition pipelines and implement trend computation.
• Ingest and normalize data from multiple upstream systems; ensure data quality and observability.
• Design APIs and the serving layer for a unified executive experience.
• Create interactive dashboards and data visualizations for senior leaders.

Skills

Systems development

Data pipelines

Python

SQL

Spark

AWS

Web dashboards

Time-series data

LLM integration

Education

Bachelor's degree in Computer Science, Engineering, or related field

Tools

Plotly

D3

Altair

QuickSight

Tableau

Streamlit

FastAPI

Flask

Job description

Amazon Data Services, Inc. is seeking a Sr. Systems Development Engineer to design, build, and own a decision intelligence platform for senior leaders across Amazon's global data center fleet.

You will design end-to-end platforms, own system architecture, and implement ETL pipelines, data models, and APIs. The role emphasizes scalable data infrastructure, automated narratives, and executive-friendly visualizations.