My daughter is making a career switch into data engineering from a completely non-science background. She already writes basic Python and SQL, but everything else—cloud services, robust pipelines, modelling, and modern storage patterns—remains a mystery to her. I want a personalised training programme that: • Builds solid foundations in data pipelines, cloud infrastructure, data modelling, and database & storage concepts. • Uses both Microsoft Azure and AWS so she can compare services and deploy end-to-end solutions on each. The format, pace, and depth are open to your professional guidance; however, by the end of the engagement she should be comfortable designing, building, and operating production-ready workflows on either platform. A brief outline of the curriculum, suggested hands-on projects, and the teaching schedule will serve as the initial milestone. Please share your résumé (or a concise summary of relevant experience) highlighting real-world data engineering work, especially where you have mentored or trained others. Practical exposure to tools such as Azure Data Factory, AWS Glue, or Apache Airflow will be a plus, as will any successful cloud migrations or large-scale pipeline implementations you have led. I’d like to review proposed session plans and see how you measure progress so we can agree on clear checkpoints before we start.