A data science team is trying to port a legacy binary classification model to Amazon SageMaker. In the legacy workflow, the data engineering component was handled using Apache Spark and scikit-learn based preprocessors. Which feature of Amazon SageMaker can be utilized for seamless integration of the legacy functionality into the new SageMaker model?