Karthik Reddy Malla

Developed & optimized scalable data pipelines using PySpark and ADF, processing 500GB+ data daily and improving processing efficiency by 40%.
Designed and implemented data models & ETL solutions, integrating on-premises SQL servers with Azure-based data warehouses, reducing data latency by 30%.
Automated data validation & error handling, reducing discrepancies by 30% and ensuring 99.9% data accuracy.
Built machine learning models using Random Forest, KNN, and Logistic Regression to predict customer revenue trends with an 85% accuracy rate.
Conducted exploratory data analysis (EDA) on large datasets using Pandas, NumPy, and Matplotlib to extract actionable insights.

Developed & optimized scalable data pipelines using PySpark and ADF, processing 500GB+ data daily and improving processing efficiency by 40%., Designed and implemented data models & ETL solutions, integrating on-premises SQL servers with Azure-based data warehouses, reducing data latency by 30%., Automated data validation & error handling, reducing discrepancies by 30% and ensuring 99.9% data accuracy., Built machine learning models using Random Forest, KNN, and Logistic Regression to predict customer revenue trends with an 85% accuracy rate., Conducted exploratory data analysis (EDA) on large datasets using Pandas, NumPy, and Matplotlib to extract actionable insights.

Developed end-to-end ETL pipelines using Python and SQL, processing structured & unstructured data from multiple sources.
Created and maintained interactive Power BI dashboards, enabling real-time business insights for 50+ stakeholders.
Designed custom PowerApps solutions, automating internal workflows and increasing operational efficiency by 25%.
Optimized query performance for large-scale datasets, reducing execution time by 35% using indexing and partitioning strategies.

Developed end-to-end ETL pipelines using Python and SQL, processing structured & unstructured data from multiple sources., Created and maintained interactive Power BI dashboards, enabling real-time business insights for 50+ stakeholders., Designed custom PowerApps solutions, automating internal workflows and increasing operational efficiency by 25%., Optimized query performance for large-scale datasets, reducing execution time by 35% using indexing and partitioning strategies.