Isha Mistry

1. Designed and maintained multiple ETL data pipelines for various data products for client using BigQuery, Dataflow and Composer to process data hosted on GCP and on prem required for building BO and Qlik dashboards. 2. Led the analysis, design and implementation team of 8 members for a crucial data pipeline product on Google Cloud Platform using technologies such as GCP BigQuery, Cloud Storage, Apache Airflow, and Ni Fi. 3. Reduced BigQuery slot consumption by 30%, optimizing query performance and cutting down job execution times by 25%. 4. Implemented GDPR compliant data pipelines within GCP to handle Right to Be Forgotten (RTBF) requests, automating the deletion of PII data from tables and performing routine data purging to ensure ongoing privacy compliance. 5. Collaborated with cross-functional teams to align data solutions with business needs and deliver high quality outcomes.

1. Developed and maintained ETL pipelines that processed over 10 million rows and 50 GB of data daily, using GCP services like BigQuery, Dataflow, and Pub/Sub. 2. Mentored 20 junior engineers on ETL best practices and acted as an SME for critical data products, guiding efficient data management strategies. 3. Acted as a Subject Matter Expert (SME) for DataStage, mentoring junior engineers and providing expert guidance on best practices. 4. Worked closely on GCP migration with cross skilled engineers to understand the on premises workflows. 5. Hands on experience on CI/CD pipelines using Jenkins, Git and Bitbucket for deployment of data applications products

1. Performing data level analysis on BigQuery data to get new insights for creating advanced applications and reports. 2. Analyzed large data volumes, identifying trends, patterns, and correlations in datasets exceeding 200 million rows. 3. Analyzed and resolved data issues in collaboration with clients, ensuring data accuracy and integrity, resulting in a 20% reduction in data discrepancies 4. Enhanced monitoring and alerting systems using GCP s Cloud Monitoring, achieving 100% uptime for critical data processes and reducing incident response times by 25%.