Business Intel Engineer, Ww Promotions and Events Data and Insights

Amazon Amazon · Big Tech · CA, BC +1 · Business Intelligence

This role focuses on business intelligence and data analysis for Amazon's promotions and events. The engineer will develop analytical reporting, conduct deep dives, and leverage LLMs to generate insights and drive growth discussions. The role also involves improving data sources and ensuring data quality. While the role uses LLMs, its core function is business intelligence and data engineering, not direct AI model development.

What you'd actually do

  1. Support business intelligence for your business and its customers.
  2. Develop, build, and deliver analytical reporting, models and business strategy
  3. Conduct deep dive analyses of business problems and formulate conclusions and recommendations to be presented to senior leadership.
  4. Leverage LLMs to generate Insights and drive growth discussions with Product teams.
  5. Produce written recommendations and insights for key stakeholders that will help shape effective metric development and reporting.

Skills

Required

  • Analyzing and interpreting data with Redshift, Oracle, NoSQL etc. experience
  • Tableau Desktop, Quicksight or other relevant data visualization software experience
  • data modeling
  • warehousing
  • building ETL pipelines
  • Statistical Analysis packages such as R, SAS and Matlab
  • SQL to pull data from a database or data warehouse
  • Python scripting to process data for modeling

Nice to have

  • Master's degree or above in BI, finance, engineering, statistics, computer science, mathematics or equivalent quantitative field
  • Microsoft Excel at an advanced level, including: pivot tables, macros, index/match, vlookup, VBA, data links, etc.
  • AWS solutions such as EC2, DynamoDB, S3, and Redshift
  • data mining
  • ETL, etc. and using databases in a business environment with large-scale, complex datasets
  • developing and presenting recommendations of new metrics allowing better understanding of the performance of the business
  • Usage of generative AI tools to enhance workflow efficiency, with a willingness to learn effective prompting and evaluation practices.
  • Ability to recognize opportunities where generative AI could enhance products, workflows, or customer experiences.

What the JD emphasized

  • strong business intelligence experience
  • entrepreneurial mindset