Hariharan VP

• · Designed and implemented robust data migration pipelines with Azure Data Factory (ADF) to transfer large volumes of on-premises data to Azure Blob Storage, ensuring data integrity and security.
• · Added columns in ADF data flows to capture metadata such as load timestamps and source system identifiers, improving data traceability and governance.
• · Implemented conditional splits within ADF data flows to route data based on predefined business rules and conditions, optimizing data processing workflows.
• · Managed scalable data warehousing solutions in Snowflake, optimizing data storage, processing, and retrieval for enhanced performance and efficiency.
• · Developed complex stored procedures and triggers in Snowflake to automate data processing workflows, enhancing data consistency and operational efficiency.
• · Designed, created, and maintained dimension and fact tables in Snowflake, employing best practices for data modeling to support accurate and efficient reporting. Implemented Snowflake Tasks to automate data loading and transformation processes.
• Designed and implemented robust ETL pipeline using Azure Data Factory and Snowflake, reducing data processing time by 60%, from 10 hours to 4 hours.

• Analyzed and tracked bug reports, leading to 35% reduction in average time to resolve critical bugs, from 20 days to 13 days.
• Developed and maintained dashboards to monitor KPIs, resulting in 25% improvement in visibility of bug resolution performance for Customer Success team.
• Conducted root cause analysis on recurring issues, reducing the number of repeat bug reports by 40%.
• Collaborated with engineering and support teams to prioritize bug fixes, leading to 50% increase in the resolution rate of high-priority issues within the first month.
• Provided data-driven recommendations that improved the overall customer satisfaction score by 15% over six months.
• Automated the bug tracking and reporting processes, saving the team 20 hours per week and increasing data accuracy by 30%.
• Analyzed customer feedback and support tickets, identifying key areas for improvement and contributing to a 20% decrease in support ticket volume related to known bugs.