Business Analyst II, Central Analytics, AET Planning & Analytics

Key job responsibilities

• Own and maintain Redshift SQL pipelines, data models, and Amazon Quick reporting dashboards that support headcount demand planning and capacity forecasting across PXT's variable workforce
• Partner with the Capacity Planning team to translate contact volume forecasts and staffing assumptions into accurate, decision-ready headcount plans
• Support Operational Planning, Quarterly Guidance, and Monthly R&O cycles by producing the data inputs, analysis, and reporting that shape headcount targets across PXT's variable workforce
• Identify, validate, and resolve data quality issues across source systems, ensuring analytical outputs are accurate and trustworthy
• Partner with Finance, HR, Operations, Data Scientists, Applied Scientists, and Business Intelligence Engineers to deliver analytical solutions that drive operational decisions
• Actively explore and integrate AI tools to automate repeatable analytical processes, improve efficiency, and enhance the quality of outputs
• Document methodology, data logic, and business rules to ensure analytical solutions are reproducible, scalable, and transferable

Basic Qualifications

• 5+ years of Excel (including VBA, pivot tables, array functions, power pivots, etc.) and data visualization tools such as Tableau experience
• 3+ years of tax, finance or a related analytical field experience
• 3+ years of business or financial analysis experience
• Bachelor's degree or equivalent
• Experience defining requirements and using data and metrics to draw business insights
• Experience with Excel
• Experience making business recommendations and influencing stakeholders
• Experience with data visualization using Tableau, Quicksight, or similar tools
• Experience with SQL
• 3+ years of SQL experience

Preferred Qualifications

• Experience in data mining (SQL, ETL, data warehouse, etc.) and using databases in a business environment with large-scale, complex datasets
• Experience with data scripting languages (e.g., SQL, Python, R, or equivalent) or statistical/mathematical software (e.g., R, SAS, Matlab, or equivalent)