Amazon - Seattle, WA

posted 9 days ago

Full-time - Mid Level
Seattle, WA
Sporting Goods, Hobby, Musical Instrument, Book, and Miscellaneous Retailers

About the position

The Sr. Business Intelligence Engineer for Workforce Analytics at AWS Industries is responsible for driving analytical thought leadership within the sales organization. This role focuses on developing insights, strategic initiatives, revenue planning, sales forecasting, and workforce analytics to optimize productivity and performance. The position requires collaboration with various teams to deliver actionable insights that support leadership in decision-making and continuous improvement.

Responsibilities

  • Building cutting-edge workforce analytics solutions to optimize productivity, capacity planning, and performance
  • Developing predictive models and data mining techniques to identify trends, opportunities, and risks across the global sales team
  • Collaborating with sales, finance, HR, Talent Acquisition, and operations leaders to align on key business questions and deliver meaningful, action-oriented insights
  • Developing a framework for the creation, tracking, and reporting of the revenue and headcount plans for the year
  • Creating mechanisms and processes to support the field sales team, maximizing their investment in time and resources
  • Supporting strategic initiatives from an analytical standpoint
  • Partnering with central economics, machine learning, data engineering, sales operations, finance, and other analytics teams to ensure efficient resource allocation
  • Ensuring quality and timeliness of analytic deliverables to meet Sales Strategy & Operations team expectations
  • Blending workforce data with sales pipeline information for accurate revenue forecasting
  • Identifying areas for process improvements and technology investments to remove barriers to sales execution

Requirements

  • 7+ years of professional or military experience
  • 5+ years of SQL experience
  • Experience with data visualization using Tableau, Quicksight, or similar tools

Nice-to-haves

  • Experience working directly with business stakeholders to translate between data and business needs
  • Experience managing, analyzing, and communicating results to senior leadership
  • Experience with theory and practice of information retrieval, data science, machine learning, and data mining
  • Experience in scripting for automation (e.g. Python) and advanced SQL skills
  • Experience with AWS technologies
  • Experience with theory and practice of design of experiments and statistical analysis of results
  • Experience programming to extract, transform, and clean large (multi-TB) data sets

Benefits

  • Flexible schedule
  • Work-life balance
  • Mentorship and career growth opportunities
  • Diverse and inclusive workplace culture
  • Employee-led affinity groups
  • Ongoing learning experiences and conferences
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