Amazon
Sr. Business Intelligence Engineer, Deal Tooling Insights, AWS GDSP Other
$130K–$203K
Boston, MA +9 · Senior · Full-time · Posted Oct 7, 2026
- Location
- Boston, MA
Austin, TX
Seattle, WA
Arlington, VA
New York, NY
Atlanta, GA
Herndon, VA
Chicago, IL
San Francisco, CA
Dallas, TX - Experience
- 10+ years of professional or military experience
- Education
- Bachelor's degree or foreign equivalent in Computer Science, Engineering, Mathematics, Statistics, Economics, or a related field
About the job
Build scalable business intelligence and analytics solutions for AWS deal tooling, producing insights and automation that inform business and leadership decisions.
What you'll do
- Design data pipelines, models, metrics, and reporting tools using large datasets; onboard new data sources.
- Analyze business problems, recommend actions, and communicate findings to senior leadership.
- Build and adopt agentic capabilities to automate reporting and answer analytical questions.
What they ask for
- Bachelor's degree or foreign equivalent in Computer Science, Engineering, Mathematics, Statistics, Economics, or a related field.
- Experience programming to extract, transform, and clean large (multi-TB) data sets.
- Scripting for automation (e.g. Python), advanced SQL skills, and experience with information retrieval, data science, machine learning, and data mining.
- Experience with data visualization using Tableau, Quicksight, or similar tools.
Nice to have
- Experience applying GenAI to improve operational efficiency and speed to insights.
- Experience building or integrating AI/ML capabilities into data platforms or analytics products (LLMs, RAG, agent frameworks, knowledge graphs, or similar).
Pay
149,900.00 - 202,800.00 USD annually (base salary); 130,400.00 - 176,300.00 USD annually (base salary); 143,400.00 - 194,000.00 USD annually (base salary)
Tools
Python, SQL, Tableau, Quicksight, GenAI, LLMs, RAG
AI focus
Build and adopt agentic capabilities to automate reporting and answer analytical questions; preferred experience includes applying GenAI and integrating AI/ML capabilities into data platforms or analytics products.
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