Rana Debnath

Engineered Python and SQL analysis workflows to process 500K+ sales records, identifying key seasonality trends that supported strategic business decision-making. Architected automated ETL pipelines using Databricks Jobs and PySpark, reducing manual reporting effort by standardizing datasets and ensuring timely data availability. Designed and deployed interactive Power BI and Tableau dashboards for 20+ stakeholders, enabling real-time tracking of KPIs and performance metrics. Key Project - Churn Prediction: Developed a machine learning-based customer churn dashboard using Python and Power BI; identified potential attrition risks and provided insights to reduce churn by approximately 15%. Key Project - Sales Performance: Analyzed historical sales data to identify high-performing regions and growth trends, delivering executive-level reporting for operational improvements.

Optimized complex SQL queries and database schemas, successfully reducing data retrieval latency by 30% for critical business reports. Collaborated effectively with backend development teams to ensure clean, reliable data ingestion pipelines for downstream BI dashboards. Led data cleaning, deduplication, and validation initiatives to improve overall data accuracy and reliability for client reporting.

Developed responsive user interfaces (UI) and optimized web performance, leveraging a deep understanding of data structures and backend workflows to enhance application efficiency. Translated technical requirements into functional software solutions, serving as a technical foundation for transition into data analytics and engineering.