Data storytelling is the skill to communicate data effectively and efficiently. Effective data storytelling goes beyond data visualization and focuses on explanations with clear rhetorical functions. It starts with data insights collected from the data science workflow. It involves iterative and interactive processes of filtering those insights into story slices, from which data stories can be created through ordering, organizing, and narration. Data storytelling is an integral component of a well-rounded data science education, which complements foundational skills like quantitative reasoning and programming. Despite its significance, a solid understanding of the theory and practice of developing data storytelling competency is lacking. Data storytelling is often perceived as a mythical process where quantitative information magically transforms into compelling narratives. Designing scalable coaching tools for data storytelling requires leveraging multidisciplinary expertise from learning science, computer science, data science, communication science, and human-centered design. In this workshop, we will share some initial findings and reflections from our interdisciplinary team searching for effective coaching methods and tools to support coaching data storytelling at scale. We will present results from literature reviews and expert interviews, which will be packaged into a set of foundational tools such as mental models, cognitive processes, and schema for story construction and assessment strategy, as well as a very early version of the platform to support the data science workflow for constructing data stories. We hope to use this workshop to build a community of researchers and practitioners in coaching data storytelling in postsecondary formal and informal learning contexts.