Venkata Charan Grandhe

I’m an experienced software engineering graduate with 1 year of hands-on experience in data engineering, backend development, and data governance within the banking domain. I enjoy turning messy data workflows into reliable, auditable systems that teams can trust.

At Perficient (BNY Mellon), I delivered end-to-end data lineage for regulatory programs aligned with BCBS 239, improving audit traceability and reducing regulatory turnaround time by 30% using Solidatus and IBM Manta. I also developed and executed UAT test cases for data lineage validation, reducing downstream defects by 35% by identifying data gaps early.

I strengthen data integrity through SQL-driven Data Quality Checks (DQCs) for critical PDEs in Collibra, reducing quality defects by 40%. I leverage advanced Excel to process CRISP datasets and translate RFIs into precise Source-to-Target (STT) mappings, accelerating upstream analysis and reducing mapping discrepancies by 25%, while building scalable ETL workflows in Informatica and integrating outputs into Power BI dashboards to improve pipeline reliability and reporting efficiency by 30%.

Earlier, as a Software Developer Intern at Avencore, I built RESTful services using ASP.NET Web API and improved data processing speed by 24%. I also designed and optimized APIs with Node.js to lower average server response time, and worked on responsive web design features that increased mobile user engagement by 36%. In my research internship at Samsung Prism R&D, I optimized a Vision Transformer model to reach 95% accuracy on the Urban 8K dataset for sound event detection, achieving 95.11% validation accuracy with Vision Transformer and 92.16% with CNN through fine-tuning and optimization.