I explained that I would start by identifying the data source and designing an ETL pipeline where data is extracted from the source, transformed using tools like Python or PySpark for cleaning and preprocessing, and then loaded into a storage system such as a data warehouse or cloud storage like Amazon S3. I also mentioned the importance of scheduling and monitoring the pipeline using tools like Apache Airflow to ensure reliability and scalability.