Developed and delivered a robust JSON Schema for mirrored Azure Databricks artifacts within the microsoft/json-schemas repository, focusing on enforcing data consistency and supporting downstream processing. The work centered on schema definition and data modeling, leveraging JSON to establish a single source of truth for mirrored artifact data. By introducing schema-based validation workflows, the developer enabled early detection of inconsistencies in the data pipeline, reducing downstream errors and validation overhead. The approach emphasized clear, traceable commits and repository governance, resulting in improved reliability for mirrored artifact pipelines and stronger data governance practices, with no major bugs addressed during this period.