Worked on the astronomer/airflow repository to enhance observability for Databricks SQL workloads by implementing session-level query tagging across SQL statements. Developed utilities for formatting and serializing query tags, ensuring seamless integration with existing Databricks SQL operators. This approach improved traceability and metadata management, making it easier to debug and monitor SQL workloads without disrupting established pipelines. The work involved updating all relevant operators to propagate and surface session tags, leveraging Python, Airflow, and SQL skills. Over the course of the month, focused on delivering this feature to support better tracking and management of session metadata within data engineering workflows.