Vijay Durga Tamirchi
Data Analyst @Visa
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WORK HISTORY
Data Analyst @Visa
Designed and maintained scalable batch ETL pipelines to ingest, parse, and transform large-scale structured and semi-structured datasets (CSV, JSON) from internal systems using AWS S3, Glue, Redshift, and Python. Built analytics-ready datasets and optimized Redshift warehouse models to support reporting, forecasting, and downstream analytical workloads.Worked closely with Data Scientists, Applied Scientists, and engineering teams to deliver high-quality data assets for predictive modeling, statistical analysis, and system simulations. Developed automated SQL and Python scripts to generate structured inputs for forecasting and decision-support use cases, focusing on efficiency, scalability, and performance.Implemented data quality checks, validation frameworks, and monitoring to ensure data accuracy and reliability across production pipelines. Contributed to data governance efforts by documenting datasets, managing metadata, supporting internal data catalogs, and troubleshooting production issues through root cause analysis while maintaining SLA compliance.
EDUCATION
Acharya Nagarjuna University
Bachelor of Technology - BTech, Electrical, Electronics and Communications Engineering
Rivier University
Master of Science - MS, Computer Science
ABOUT VIJAY DURGA TAMIRCHI
Data Analyst with 3+ years of experience delivering AI/ML-driven analytics and cloud-based data solutions in financial services. Strong expertise in fraud analytics, predictive modeling, ETL pipelines, and large-scale transaction data processing.At Visa, I work with high-volume payment transaction data to design and maintain end-to-end data pipelines, fraud detection models, and real-time monitoring systems. I use Python, SQL, PySpark, XGBoost, TensorFlow, and Azure Databricks to improve fraud detection accuracy, resulting in a 22% reduction in fraudulent chargebacks. Optimized ETL workflows improved pipeline performance by 55%.Previously at Wipro, I supported financial services clients by automating data ingestion pipelines, building Power BI and Tableau dashboards, and optimizing AWS Redshift data warehouses. Developed predictive models for churn analysis and demand forecasting to support business planning and risk assessment.Technical skills include Python, SQL, Power BI, Tableau, machine learning, fraud and risk analytics, ETL, data pipelines, Azure, AWS, and cloud data warehousing. Experienced in working cross-functionally with engineering, product, and business teams.Seeking Data Analyst, Fraud Analyst, or AI/ML Analytics roles in data-driven organizations.
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