• Leveraged advanced analytical techniques and data modelling to support the migration of financial technology projects of Citi Bank, improving performance and scalability.• Optimized data management using Azure Data Lake Storage, reducing storage costs by 30%.• Designed and implemented robust ETL pipelines using Azure Data Factory, resulting in improvement in workflow efficiency.• Implemented automated monitoring solutions with Azure Monitor and Application Insights, reducing incident response times by 50% and enhancing system reliability.• Utilized SQL and DAX to optimize query performance, manage databases, and perform data analysis, which reduced the time required for generating financial reports by 3.5 hours.• Implemented data visualization solutions with Power BI, integrating KPIs that led to a 10-hour weekly reduction in manual reporting efforts.• Applied Python libraries (Pandas, NumPy, Matplotlib) for statistical analysis and data processing, enhancing the ability to provide actionable insights and support data-driven decision-making.• Systemized data extraction processes using SQL Server Management Studio (SSMS), which streamlined data management and reporting tasks.• Assisted in resolving production support issues and addressing data discrepancies, ensuring data integrity through testing.

• Explored and analyzed Citi Bank datasets using Power BI to extract actionable insights and visualizations, enhancing data-driven decision-making processes.• Applied advanced SQL queries to optimize data retrieval and perform in-depth analysis, improving the efficiency and accuracy of data operations.• Utilized Python for data cleaning, ETL processes, and visualization, ensuring data integrity and effective transformation for subsequent analysis.• Validated analytical outcomes by cross-referencing results with other platforms, ensuring consistency and reliability of insights.

• Assisted in analyzing large data sets to identify trends, patterns, and insights, supporting the team’s decision-making process.• Created and maintained detailed reports and dashboards to track key performance metrics and project progress.•Created interactive dashboards and reports, including a Pizza Sales Analysis Dashboard using SQL and Power BI, and a Loan Eligibility Prediction utilizing Python libraries like pandas and matplotlib. These projects featured dynamic visualizations and KPIs to provide actionable business insights and academic performance analysis.