Senior Business Intelligence Engineer, Devices Demand Science Optimization

Amazon Amazon · Big Tech · Seattle, WA · Business Intelligence

This role focuses on building AI-powered data products and automating business workflows using GenAI. The engineer will design and maintain data pipelines and semantic layers to make data accessible to AI agents, and integrate AI features into BI solutions. The role is at the intersection of analytics, data engineering, and AI, aiming to scale business intelligence across multiple teams.

What you'd actually do

  1. Design, build, and maintain scalable core data tables and pipelines that serve as the single source of truth for Devices sales, inventory, pricing and demand planning metrics.
  2. Automate reporting workflows and data processes to reduce manual effort and improve speed, accuracy, and reliability of insights delivered to stakeholders.
  3. Build and integrate AI powered features into BI solutions, including intelligent agents, automated callouts, and generative AI driven summaries that surface key insights proactively.
  4. Partner with stakeholders across demand planning, forecasting, and inventory teams to translate business requirements into well scoped, long term, AI-driven data solutions.
  5. Design and manage pipeline orchestration to coordinate data ingestion, transformation, and delivery across multiple systems and schedules.

Skills

Required

  • 10+ years of professional or military experience
  • 7+ years of SQL, ETL or Oracle experience
  • 7+ years of processing large, multi-dimensional datasets from multiple sources experience
  • 5+ years of developing automated reporting experience
  • Experience with AWS technologies
  • Experience in scripting for automation (e.g. Python) and advanced SQL skills.
  • Experience with data visualization using Tableau, Quicksight, or similar tools
  • Knowledge of data warehousing and data modeling
  • Experience working directly with business stakeholders to translate between data and business needs

Nice to have

  • Experience managing, analyzing and communicating results to senior leadership
  • Experience programming to extract, transform and clean large (multi-TB) data sets
  • Experience with theory and practice of information retrieval, data science, machine learning and data mining

What the JD emphasized

  • AI-powered data products
  • AI agents
  • GenAI

Other signals

  • AI-powered data products
  • GenAI automation
  • AI agents
  • generative AI driven summaries