Asvitha V S

-Designed and automated batch data pipelines to process large-scale, multi-source digital advertising data, enabling daily computation of impressions, reach, and unique user metrics used in Digital Ad Ratings (DAR). -Implemented data quality validation rules, anomaly detection checks, and exception-handling workflows, ensuring high data integrity and increased client confidence in delivered metrics. -Automated multiple manual and operationally heavy processes, including routine data processing tasks and pipeline triggers, significantly reducing manual intervention and operational overhead. -Developed failure-handling mechanisms by analyzing Spark and Airflow logs, classifying expected vs. unexpected failures, and enabling automated retries or alerting mechanisms. -Implemented an SLA breach monitoring framework to proactively detect delays in data availability and notify relevant teams, eliminating the need for continuous manual monitoring. -Optimized Spark transformations and Airflow DAGs to reduce pipeline failures and improve processing performance. -Collaborated closely with cross-functional teams (engineering, analytics, and product stakeholders) to support end-to-end delivery of reliable ad performance insights.