You have built a machine learning model that is trained on data stored in Parquet files. This data is accessed through a Hive table hosted on Google Cloud Platform (GCP). For preprocessing, you utilized PySpark and exported the resulting data as a CSV file into Google Cloud Storage. Following this preprocessing stage, you perform additional steps to train and evaluate your model. You now wish to automate and parameterize this entire model training workflow using Kubeflow Pipelines on Google Cloud. What should you do to achieve this?