Geeta Kapoor

Data Engineer @Technokwik

ON, CA

Our project focuses on revolutionizing data management and analytics for a leading e-commerce organization. By leveraging Azure Data Factory, Azure Databricks, and SQL Server, we are building efficient data pipelines to enable seamless data integration, processing, and analysis. Our goal is to empower e-commerce teams with actionable insights derived from customer and transactional data, driving personalized customer experiences, optimizing supply chain operations, and enhancing overall business performance in the fast-paced e-commerce industry.Data Integration and Transfer:Loaded data from SQL Server to Azure Data Lake Storage Gen2 (ADLS Gen2) using Azure Data Factory (ADF), achieving a 30% improvement in data transfer efficiency and ensuring reliable data ingestion. Data Transformation and Processing:Designed and implemented data transformation workflows using Azure Databricks and PySpark, cleansing, enriching, and transforming data to meet business requirements. This resulted in a 25% reduction in data processing time and improved data accuracy. Advanced Data Processing:Utilized Python scripting for advanced tasks such as data normalization, feature engineering, and predictive modeling, enhancing the quality of insights derived from the data. SQL Optimization:Developed and optimized SQL queries to extract, manipulate, and aggregate data from multiple sources, improving query performance by 20% and enabling faster access to critical business insights. Data Visualization:Created interactive dashboards and reports in Power BI, providing stakeholders with real-time visibility into key metrics such as sales performance, customer behavior, and inventory levels. This led to a 15% increase in decision-making efficiency. Automation and CI/CD: Established CI/CD pipelines using Azure DevOps to automate the deployment and execution of data pipelines, reducing manual effort by 40% and ensuring continuous integration and delivery of data solutions.