Senior Business Intelligence Engineer, Smgs Ops - Sales Planning & Compensation

Amazon Amazon · Big Tech · Arlington, VA · Business Intelligence

This role is for a Senior Business Intelligence Engineer focused on Sales Planning & Compensation within AWS SMGS. The primary responsibilities involve working with large datasets, writing SQL queries, building data models with Python, and partnering with business owners to integrate ML and generative AI into scaling programs. The role requires strong analytical and statistical rigor to drive business decisions and communicate complex results. While the role mentions integrating ML and generative AI, its core function is BI engineering and data analysis, not direct AI/ML model development.

What you'd actually do

  1. Work directly with the models/data. Work with large data sets and the technical tools needed to work with them
  2. Write high quality SQL queries to retrieve and analyze data from database tables (ex. Redshift, MySQL). Build data models leveraging Python.
  3. Partner with business owners, tech and central teams to integrate machine-learning, generative AI, and automation into scaling our programs and processes
  4. Use analytical and statistical rigor to solve complex problems and drive business decisions
  5. Drive towards simple, scalable solutions to difficult problems

Skills

Required

  • 5+ years of SQL, ETL or Oracle experience
  • 5+ years of performing statistical analysis experience
  • 1+ years of developing automated reporting experience
  • 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

Nice to have

  • Experience working directly with business stakeholders to translate between data and business needs
  • Experience managing, analyzing and communicating results to senior leadership
  • Master's degree in statistics, data science, or an equivalent quantitative field
  • Experience in scripting for automation (e.g. Python) and advanced SQL skills.

What the JD emphasized

  • Work directly with the models/data
  • Work with large data sets
  • integrating machine-learning, generative AI, and automation