Anuhya Y

Sep 2024 – Jun 2026 | Hybrid | Irving, TX

• Developed and maintained scalable data pipelines to support banking applications by integrating data from multiple enterprise systems using Python, SQL, and cloud technologies.
• Built ETL workflows for extracting, transforming, and loading structured banking data into analytical systems, enhancing data accuracy and consistency for improved decision-making.
• Designed and optimized SQL queries for data extraction, transformation, reporting, and performance improvements across large datasets.
• Worked with production data workflows, batch processing jobs, and application integrations to support business-critical financial systems.
• Implemented data quality checks and monitoring processes to identify data issues, increasing reliability of downstream applications and supporting compliance with regulatory standards.
• Developed Python-based automation scripts for data validation, application health checks, and operational monitoring, reducing manual support activities.

• Developed SQL queries for data analysis and validation, generating actionable business insights from structured datasets.
• Contributed to building ETL workflows that cleaned, transformed, and prepared data for reporting and analytics.
• Developed Python-based data processing scripts to extract, transform, and validate application data from multiple sources.
• Integrated application data between internal systems and external services using REST APIs.
• Performed data quality checks and debugging activities to improve accuracy and reliability of processed data.
• Collaborated with development teams using Agile methodologies, Git, and Jira for task management and delivery.

• Developed SQL-based data transformations and supported ETL processes for enterprise applications in the financial services domain.
• Optimized SQL queries and database operations, enabling faster access to critical business reporting.
• Integrated data from multiple sources and performed data cleansing, transformation, and quality validation activities.
• Created Python scripts for data extraction and validation, enhancing accuracy of reporting and analytics.
• Monitored data workflows, troubleshooting and resolving issues to ensure data integrity and reliability.
• Participated in Agile ceremonies and collaborated with technical teams to deliver data solutions.

• Developed data pipelines for processing and transforming application data using Python and SQL, enhancing data accessibility.
• Executed data cleaning, validation, and transformation activities, resulting in higher data quality and reliability.
• Developed scripts to automate repetitive data processing and reporting tasks.
• Worked with relational databases to write queries and support application data requirements.
• Collaborated with engineering teams to gather data requirements and implement tailored solutions, ensuring alignment with project objectives.