✦ Luna Orbit — Data & Analytics

Business Intelligence Engineer II, Central Data Engineering and Analytics

at Amazon.com

📍 US, WA, Seattle Unknown Posted March 24, 2026
Type Not Specified
Experience mid
Exp. Years Not specified
Education Not specified
Category Data & Analytics

This role involves developing AI-powered analytics platforms for retail, focusing on natural language querying, semantic layers, and large dataset management to support decision-making.

  • Design knowledge bases
  • Develop conversational interfaces
  • Build metrics and dashboards
  • Enable natural language querying
  • Collaborate with retail teams

The technical environment includes SQL, Oracle, NoSQL databases, AI and NLP tools, with a focus on conversational analytics, metrics, dashboards, and large data processing.

The ideal candidate is a mid-level business intelligence engineer with experience in SQL, ETL, and AI-driven analytics, especially in natural language processing and conversational interfaces, supporting retail data insights.

SQLETLData analysisAINatural language processing
Conversational interfacesAI-driven insightsSemantic layersKnowledge basesLarge datasets
RedshiftOracleNoSQL databasesAI platformsNatural language processing tools
SQLETLOracleNoSQLData analysisAINatural language processingDashboardsReportsSemantic layers
SQLETLOracleNoSQLData analysisNatural language processingAIMachine learningData foundationsConversational analyticsMetricsDashboardsReports
CollaborationAnalytical thinkingCommunicationProblem-solvingTeamwork
Industry Retail / E-commerce / Technology
Job Function Create AI-driven retail analytics and conversational platforms
Role Subtype Business Intelligence Engineer
Tech Domains SQL / PostgreSQL, Oracle, NoSQL, AI, Natural language processing
Business Intelligence EngineerSQLETLOracleNoSQLData analysisAINatural language processingConversational analyticsMetricsDashboardsReportsAI-driven insightsSemantic layersKnowledge basesLarge datasets

Lack of experience with SQL or ETL, No AI or NLP experience, No experience with large datasets, Must be authorized to work in the US

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