Ritik Agarwal

Level 3 Support (L3):

• Led troubleshooting and root cause analysis of complex data pipeline issues within Azure Data Services, ensuring minimal downtime and swift issue resolution.
• Supported and maintained production environments in Azure, resolving high-priority incidents and implementing corrective measures for ongoing system stability.
• Identified and resolved performance bottlenecks in data integration processes using Azure Data Factory , SQL Server , and SSIS .
• Collaborated with development teams to optimize and resolve data integration challenges, including improving ETL workflows and data processing efficiency .
• Provided in-depth troubleshooting support for issues related to data integrity , data synchronization , and cloud-based data storage .
• Worked on complex SQL query optimization, database performance tuning, and SSIS troubleshooting to resolve critical production issues in a timely manner.
• Conducted root-cause analysis of data flow issues, making recommendations for system improvements and implementing fixes.

Level 2 Support (L2):

• Responded to and managed moderate-level technical issues , providing support for Azure Data Factory, Azure SQL Database , and SSIS .
• Assisted with the monitoring and maintenance of cloud-based data infrastructure, resolving data pipeline failures and alerts for ETL and data synchronization processes.
• Conducted data validation and error resolution to ensure data accuracy and availability across various Azure data services.
• Provided ongoing support for data migration projects by resolving issues related to cloud storage, data integration, and database compatibility.
• Monitored and supported data pipelines running on Azure Data Factory, ensuring smooth execution and identifying potential bottlenecks.
• Collaborated with cross-functional teams (DBAs, developers, business users) to understand system requirements and resolve data-related issues.
• Actively resolved incidents, managed tickets, and troubleshot issues, including pipeline failures, performance issues , and data mismatches.
• Supported the management of Azure Data Lake and Blob Storage environments, ensuring optimal data storage and retrieval for pipeline processes.
• Led the migration of legacy on-premises ETL solutions to Azure Data Factory for improved scalability and flexibility.
• Developed SQL queries to validate the data post-processing.
• Participated in the optimization of data workflows and troubleshooting of complex issues related to data processing pipelines.
• Documented and communicated database schemas using accepted notations.
• Provided technical guidance and mentorship to junior team members, fostering a collaborative learning environment within the organization.