Describe a comprehensive feature engineering pipeline for a dataset consisting of multivariate time-series data with irregular sampling rates. Detail how to create lag features, rolling window statistics (mean, standard deviation, skewness), and Fourier transform components to capture cyclical patterns. Additionally, explain how to handle missing data points without introducing bias into the model training set.