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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.

At Auctane, when during the re-architecture presentation I presented that we should be using ElasticSearch for advanced search and reporting features - a Sr. Manager from another team challenged this choice and said that it cannot serve, the company had tried to host and operate in our Data center before and failed - I had this data and presented that facts - I told that ELK cluster can scale horizontally and since this time we would be using AWS managed Elastic Search operations would reduce for our team. By preparing for this meeting and having some prior knowledege did help me answer this question and gain trust by the larger team.