Drimva

Amazon

Senior BIE, Business Intelligence & Analytics (BIA)

$130K–$176K

Seattle, WA · Senior · Full-time · Posted Oct 23, 2026

Experience
10+ years of professional or military experience; specified 8+ years in SQL, large multidimensional datasets, statistical analysis, and a related occupation.
Education
Bachelor's degree or foreign equivalent in Computer Science, Engineering, Mathematics, Statistics, Economics, or a related field.

About the job

Leads development of governed, AI-powered analytics and automation for AWS Platform Experience to support executive decisions and revenue assurance.

What you'll do

  • Own the analytics stack roadmap, data models, semantic layers, governance, and AI integration patterns.
  • Build AI-driven root-cause investigation, anomaly detection, and proactive insight products; automate recurring reports.
  • Set metric governance and technical standards, assess statistical methods and AI outputs, and mentor engineers while aligning stakeholders.

What they ask for

  • Bachelor's degree or foreign equivalent in Computer Science, Engineering, Mathematics, Statistics, Economics, or a related field.
  • 8+ years of SQL experience; 8+ years processing large, multi-dimensional datasets from multiple sources; and 8+ years performing statistical analysis.
  • 8+ years as a Data Analyst, Data Engineer, Business Intelligence Analyst, or related occupation.
  • Experience programming to extract, transform, and clean large (multi-TB) datasets; data visualization with Tableau, Quicksight, or similar; AWS technologies; and automation scripting (e.g. Python) with advanced SQL skills.

Nice to have

  • Master's degree in a related field.
  • Experience with information retrieval, data science, machine learning, and data mining; or as a BIE in a technology company.

Pay

130,400.00 - 176,300.00 USD annually (base salary)

Tools

Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Amazon Redshift, Athena, SQL, Tableau, Quicksight, Python

AI focus

Develops AI-powered analytics for root-cause investigation, anomaly detection, and proactive insights, using LLMs, RAG, and agent frameworks; evaluates AI outputs for accuracy, auditability, and trust.

Model-written summary · the original posting is authoritative

First seen Oct 24, 2026 · Last verified Nov 5, 2026 (UTC)