Debarshi Nandan

Served as technology authority for cloud metadata, catalog, profiling, lineage, and AI-assisted reverse-engineering in erwin Data Intelligence Suite. Architected GenAI/LLM pipelines with Azure OpenAI, achieving 82% prompt cache-hit rate and leading architecture reviews, release certification, and mentoring.

Built analytics, metadata automation, and data-lineage solutions using Python, SQL, machine learning, and data profiling. Translated business requirements into production-ready designs and validation workflows.

Led Data Vault and Business Vault automation programs. Designed data pipelines, validation logic, analytics, and data-mining workflows across healthcare, retail, and education domains.

Designed SQL Server/SSIS warehouse-loading architectures with automated validation, failover, and recoverable processing. Improved churn-prediction performance by 25% using decision-tree and clustering models.

Planned regulated healthcare data migrations, reconciliation, reporting, and client customization. Mentored and led a team of six analysts.

Developed single sign-on authentication/authorization for web applications. Contributed to object-oriented architecture and data-model design.

Pursued M.Tech in Data Science and Engineering, completed in July 2026.

Completed the Neural Networks for Machine Learning certification in 2015.

Completed B.Tech in Electronics and Communication Engineering from 2002 to 2006.