Upender S.

Created and launched Power BI dashboards featuring custom DAX measures and Power Query to track over 15 sales KPIs, enhancing business visibility by 30%. Implemented automation for more than 10 recurring weekly reports utilizing Python and SQL, resulting in a weekly savings of over 15 hours and minimizing manual effort by 90%. Developed and upheld end-to-end ETL pipelines integrating multiple data sources into a centralized data warehouse, which led to an 80% decrease in data processing time. Improved complex SQL queries through advanced indexing and restructuring, achieving a 25% enhancement in performance. Established automated systems for data quality monitoring to identify anomalies, ensuring accurate reporting across dashboards. Created analysis pipelines for competitive and market research using Selenium, BeautifulSoup, and PySpark, saving over 10 hours weekly in manual tasks. Conducted Exploratory Data Analysis (EDA) utilizing Python, Pandas, and PySpark to identify trends and provide actionable insights.

Engineered scalable ETL pipelines leveraging PySpark to facilitate efficient high-volume data processing. Designed data models in SQL and Python to optimize workflows, leading to a 15% reduction in reporting errors. Constructed interactive dashboards in Power BI and Excel for monitoring KPIs and deriving business insights. Managed the cleaning, transformation, and loading of both structured and unstructured data, ensuring data accuracy, consistency, and integrity.