Compensation Data Systems and Automation Questions

This topic covers practical skills for managing compensation data and automating compensation processes. Candidates should demonstrate the ability to extract and transform data from human resources information systems and payroll systems using Structured Query Language, automate repeatable analyses and data preparation tasks using Python or similar scripting languages, build reproducible data pipelines with validation checks, integrate external market data, and design efficient workflows for annual compensation reviews, benchmarking, and reporting. Candidates should also be able to identify process inefficiencies and implement technical solutions that reduce manual effort, improve accuracy, and preserve data privacy and auditability.