• Led Fraud Detection System Project: Developed a system using MySQL, Python, and Tableau to analyse 10M+ e-commerce transaction records, identify fraud patterns, reduce fraudulent activities by 30%.• Designed and Implemented Database Schema: Created an optimized schema in MySQL and SQL Server to store and query large datasets (10M+ records) efficiently, ensuring data integrity and improving query performance by 40%.• Enhanced Data Visualization: Built interactive dashboards in Tableau Desktop and Microsoft Power BI for real-time monitoring and reporting, reducing fraud detection response time by 25%.• Collaborated with Cross-Functional Teams: Worked with 5+ engineering and operations teams to integrate fraud detection algorithms into the existing e-commerce transaction processing system, enhancing collaboration and communication.• Conducted Data Wrangling and Cleaning: Utilized R packages (dplyr, tidyr) and Python libraries (Pandas, NumPy) to clean and prepare data, improving data quality by 20% and reducing data processing time by 15%.• Performed Statistical Analysis: Used R and Python for statistical analysis and modelling, including time series analysis with forecast and tseries packages, enhancing prediction accuracy by 25%.• Utilized ETL Tools: Employed Tableau Prep and Talend for ETL processes, enhancing data integration efficiency by 25%.• Enhanced Data Workflow Automation with Alteryx: Utilized Alteryx to streamline and automate complex data workflows, reducing manual data processing by 30% and improving data preparation for real-time reporting.• Orchestrated ETL Pipelines Using Apache Airflow: Implemented Apache Airflow to manage and automate ETL workflows, ensuring smooth and timely data ingestion from MySQL to AWS Redshift, reducing data latency by 25%.• Integrated CI/CD Processes: Automated deployment of data pipelines using Jenkins, reducing deployment time by 40% and ensuring consistent updates across platforms.

Led a Fraud Detection Project that reduced fraudulent activities by 30% by developing a system using MySQL, Python, and Tableau to analyze over 10M transactions. Optimized database performance with a MySQL schema redesign, improving query speed by 40%, and enhanced real-time reporting through interactive dashboards in Tableau and Power BI, cutting response time by 25%. Improved data quality by 20% and reduced processing time by 15% through data wrangling in R and Python.Led a Fraud Detection Project that reduced fraudulent activities by 30% by developing a system using MySQL, Python, and Tableau to analyze over 10M transactions. Optimized database performance with a MySQL schema redesign, improving query speed by 40%, and enhanced real-time reporting through interactive dashboards in Tableau and Power BI, cutting response time by 25%. Improved data quality by 20% and reduced processing time by 15% through data wrangling in R and Python.

• Development and Optimization of SQL Queries: Created and optimized 50+ SQL queries for data extraction, transformation, and loading, improving query performance by 30%.• Collaborated with Senior Data Engineers: Worked with a team of 5+ senior data engineers to troubleshoot and resolve data-related issues, reducing downtime by 20%.• Utilized Python for Data Cleaning and Analysis: Employed Python (Pandas, NumPy) to clean, analyse, and manipulate datasets (1M+ records), enhancing data processing efficiency by 25%.• Created and Maintained Data Visualizations: Developed and maintained 15+ dashboards and visualizations using Tableau and Power BI to support data-driven decision-making, improving reporting accuracy by 20%.• Data Transformation and Automation with Alteryx: Applied Alteryx to blend and transform data from various sources, automating repetitive data preparation tasks and improving ETL efficiency by 35%.• Scheduled and Monitored Data Pipelines with Apache Airflow: Used Apache Airflow to schedule and monitor automated data pipelines, ensuring reliable data transfer between systems and reducing downtime by 20%.• Conducted Data Quality Assessments: Performed data quality assessments on 10+ datasets, implementing measures to ensure data accuracy and integrity, reducing data errors by 15%.• Assisted in Designing and Implementing ETL Pipelines: Helped design and implement 5+ ETL pipelines, ensuring seamless data integration from various sources and reducing data integration time by 25%.• Managed Big Data Technologies: Gained hands-on experience with Apache Spark, Hive, and Kafka for handling large datasets, improving data processing capabilities by 20%.