Sr. Business Intelligence Engineer , Aws Gdsp 3px

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

Senior Business Intelligence Engineer role focused on Private Pricing Analytics within AWS GDSP. Responsibilities include developing analytical and forecasting models, creating self-service dashboards and visualizations, and implementing automation solutions to drive process improvements. Requires strong business acumen, analytical background, and experience translating business requirements into actionable solutions. Basic qualifications include experience with statistical analysis, scripting for automation (Python), advanced SQL, information retrieval, data science, machine learning, data mining, working with business stakeholders, and data visualization tools (Tableau, Quicksight).

What you'd actually do

  1. Lead business discussions to share insights, challenge status quo, and provide forward looking recommendations to enable strategic decision making and growth of Private Pricing.
  2. Support the development of continuously-evolving business analytics and data models, own the quantitative analysis of the performance of our sales team, customers, deal team, partners, markets, and products/services.
  3. Develop a deep understanding of sales metrics, reporting tools, and data structures in order to identify and drive resolution of issues, provide actionable intelligence with existing metrics or identify, develop, and propose new metrics, dashboards, scorecards or new tools.
  4. Develop relationships and processes with sales, finance, sales operations, and other functional teams to identify and address reporting issues.
  5. Manage and develop analytical tools or reports that through the automation existing inspection mechanisms such as business reviews, annual planning, and forecasting processes.

Skills

Required

  • Experience with theory and practice of design of experiments and statistical analysis of results
  • Experience in scripting for automation (e.g. Python) and advanced SQL skills.
  • Experience with theory and practice of information retrieval, data science, machine learning and data mining
  • Experience working directly with business stakeholders to translate between data and business needs
  • Experience with data visualization using Tableau, Quicksight, or similar tools

Nice to have

  • Experience managing, analyzing and communicating results to senior leadership
  • Master's degree in statistics, data science, or an equivalent quantitative field

What the JD emphasized

  • deep understanding of customer and business priorities
  • thorny business challenges
  • dynamic environment
  • diverse teams
  • common goal
  • highest standards of excellence
  • broad technical skills
  • strong business acumen
  • deep analytical background
  • actionable solutions
  • deep understanding of the AWS Private Pricing business
  • relevant and actionable
  • building analytical and forecasting models
  • intuitive self-service dashboards and visualizations
  • automation solutions
  • process improvements
  • communicate effectively across multiple technical and non-technical business units
  • across other geographies
  • collaborate effectively
  • solve data problems
  • implement new reporting solutions
  • deliver successfully against high operational standards
  • highly motivated individual
  • tell the story” of the data
  • little direction or supervision
  • high degree of ambiguity
  • lead business discussions
  • share insights
  • challenge status quo
  • forward looking recommendations
  • strategic decision making and growth
  • continuously-evolving business analytics and data models
  • quantitative analysis
  • sales team, customers, deal team, partners, markets, and products/services
  • deep understanding of sales metrics, reporting tools, and data structures
  • identify and drive resolution of issues
  • actionable intelligence
  • existing metrics
  • identify, develop, and propose new metrics, dashboards, scorecards or new tools
  • Develop relationships and processes
  • sales, finance, sales operations, and other functional teams
  • identify and address reporting issues
  • Manage and develop analytical tools or reports
  • automation
  • existing inspection mechanisms
  • business reviews, annual planning, and forecasting processes
  • Create operational templates and processes
  • compile and standardize disparate information
  • standardized reporting and metrics tracking
  • Generate ad-hoc analysis and reports
  • actionable recommendations
  • needs of the stakeholders
  • ad-hoc data retrieval and analysis
  • data management systems
  • Create new mechanisms and business processes
  • simplifies, standardizes and enables operational excellence
  • driving deal strategy, structuring, negotiations, and execution
  • private deals
  • large, strategic, or highly competitive commercial deals
  • theory and practice of design of experiments
  • statistical analysis of results
  • scripting for automation
  • advanced SQL skills
  • theory and practice of information retrieval, data science, machine learning and data mining
  • working directly with business stakeholders
  • translate between data and business needs
  • data visualization
  • Tableau, Quicksight, or similar tools
  • managing, analyzing and communicating results to senior leadership