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l, I initially built automation scripts for trade reconciliations and reporting using standalone Python and UNIX-based cron jobs. These worked well for smaller data volumes, but as our operations scaled across global teams in London, Hong Kong, and the Bahamas, performance and maintainability became a bottleneck.

I realized I needed to adapt my workflow to better support large-scale, distributed processes. So, I changed how I worked by migrating critical pipelines from PostgreSQL and flat scripts into a more robust ETL framework using Databricks and Delta Lake. I restructured batch processes into streaming jobs and modularized the Python code to be production-grade. I also started using Kafka and Kubernetes to improve system reliability and orchestration.

In my current role, there was a time when operation and engineering team was not aligned which was causing lots of delays during deployment. as per operation team build should be deployed in same branch which was available on pre-prod but as we were running multiple projects/features parallelly. it was difficult to develop and test everything in one branch and made it ready for deployment in a short time.

I had to work with my team (engineering team) and operational team to come up with a solution where we both are aligned and can reduce delivery time as well.

Initially i had proposed a solution when we were developing and testing work on feature branch and once its fully tested by QA on feature branch we push all changes to staging branch where we can do final testing. for some time this approach worked but we start facing new issue which is related to code merge as after merge features were impacting each other and require additional time to fix those issues and make it ready within planned time.

We added one more process if features/fixes are small and won't impact much then we merge else we try to plan deployment sequentially to avoid any further delay. 

This approach helped team to deliver project/feature on time and operational team was happy as they don't need to keep track of multiple branches during deployment.