Worked on enhancing documentation for Iceberg-based data partitioning and scanning within the chalk-ai/docs repository, focusing on improving clarity for data engineers. Addressed how custom partition mappings interact with transformed timestamp columns to support more effective partition pruning, and refined explanations of filter behavior across partitions. Used Markdown and Python to implement targeted updates, ensuring technical accuracy and reducing ambiguity in onboarding materials. The work involved two precise documentation commits, emphasizing both grammar and conceptual clarity. These improvements aimed to streamline developer onboarding and minimize misinterpretations, supporting data engineering workflows by making complex partitioning and scanning concepts more accessible and actionable.