DATEV eG is processing monthly 15 mio. payslips of German employees. We present a privacy-preserving way to learn a machine-learning model on this sensitive data and a product to assess if the salary of current/prospective employees is in line with the market. Besides data engineering and machine learning, this talk focusses on anonymisation, namely differential privacy in combination with privacy amplification and highlights the learnings as an organisation to build data-driven products.