Yaswant is a Python Developer with 7+ years of experience in backend development, specializing in Python, Django, and cloud deployments. He has a strong track record in production support and data processing across various domains.
Optimized handling of millions of records through multi-threading in AKS for high-volume batch processing.
Developed proprietary Django-based tools for efficient data organization and automated report generation.
Engineered Python automation scripts for rerun failed Control M jobs, significantly reducing manual intervention.
Managed application deployments leveraging CI/CD pipelines into Azure App Service.
Successfully executed data migrations between diverse database systems including Snowflake to Aerospike.
Built Feedback App — feedback on ML/Business rules predicted values + Snowflake DB feedback loop as Software Developer
Built Master Patient Index (MPI) — patient demographic values in Aerospike for TEFCA QUEEN framework as Software Developer
Built Global Data — web scraping career portals + company websites for IC Tool data analytics consulting as Web Scraping Developer
Built SERP Accounting — Society for Elimination of Rural Poverty (SERP) transactions + loans + savings + balance sheets + loan ledgers + EMI schedules as Backend Developer
Built HSBC-UKBI — UK BI for HSBC supporting millions of customers across 67 countries + liquidity management + AML reporting as ETL Support Engineer
Overview: Developed a feedback application allowing users to update feedback on ML/Business rules predicted values for transaction categories. Responsibilities: Developed a dynamic data model enabling configuration-driven page creation for flexible UI generation. Implemented business logic in Python Flask to process feedback and update predictions in the database. Managed the deployment of the application using CI/CD pipelines into Azure App Service.
Key outcomes:
Developed a dynamic data model enabling flexible UI generation without hardcoding layouts or components.
Managed application deployment using CI/CD pipelines into Azure App Service.
Overview: Developed a Master Patient Index (MPI) to store unique patient demographic values in Aerospike, essential for the TEFCA QUEEN framework. Responsibilities: Developed FastAPI applications to execute patient matching algorithms and update demographic data, returning matched patient IDs. Performed indexing on Aerospike sets and implemented Python business logic for data retrieval and updates.
Key outcomes:
Optimized batch processing by implementing multi-threading in AKS for millions of records.
Successfully migrated data from Snowflake to Aerospike.
Overview: Worked on a project to scrape and process data from various career portals and company websites. Responsibilities: Developed web scraping solutions for gathering and analyzing data from client websites and managed script scheduling. Used Selenium and Scrapy to extract website data and insert it into MS SQL database.
Key outcomes:
Created a proprietary Django-based tool for efficient data organization and reporting for client use.
Automated scheduled tasks on various VMs to streamline data collection and analysis processes.
Overview: Developed an accounting system for the Society for Elimination of Rural Poverty (SERP) to manage transactions, loans, and savings data. Responsibilities: Designed database tables and developed stored procedures (PL/SQL) for business logic implementation and report generation. Optimized SQL queries for efficient data retrieval from backend databases to the UI.
Key outcomes:
Optimized SQL queries for efficient data retrieval.
Generated various financial reports and made them web-accessible using Django.
Overview: Supported HSBC's UKBI, an authorized data store for business intelligence, serving millions of customers across 67 countries. Responsibilities: Supported batch mode ETL - Datastage jobs round the clock. Proactively analyzed and resolved production issues, identifying root causes and recommending appropriate fixes.
Key outcomes:
Proactively resolved production issues to ensure system stability and minimize downtime.
Automated failed Control M jobs using Python scripts, reducing manual intervention and improving efficiency.
Yaswant
Python Developer