Worked on enhancing observability for distributed Spark workloads by addressing a critical bug in the getsentry/sentry-python repository. Focused on the Sentry Python Spark integration, the developer resolved an initialization timing issue that previously prevented reliable tracing when SparkContext was created in varying orders. The solution involved refactoring the integration to activate after SparkContext creation, ensuring consistent tracing setup. Additionally, helper utilities were introduced to streamline activation and patching processes for SparkContext initialization. Leveraging skills in Python, distributed systems, and integration development, the work improved debugging capabilities and maintainability for Spark jobs, with an emphasis on robust testing and code clarity.