Shawn Urinov

Sr Bi Developer @HUB International

Chicago, IL, US

Optimized slow-performing queries in Azure SQL Database by removing redundant joins and unnecessary data type conversions, significantly improving query execution times.Developed ad-hoc SQL queries to support dynamic and on-demand reporting requirements.Collaborated with business stakeholders to gather requirements and translate them into scalable data solutions, ensuring alignment with reporting and analytics goals.Automated monthly report generation by building Azure Data Factory (ADF) pipelines and integrated notebooks, delivering Excel reports to stakeholders on schedule.Designed Python scripts to streamline data handling by loading CSV files into formatted Excel sheets, merging datasets, splitting large files across multiple sheets, and organizing sheet order for clarity.Refactored legacy SQL queries by introducing parameterization, enabling reusable and dynamic data extraction without manual filter changes.Built execution logging mechanisms within ADF pipelines to track run details and store them in SQL log tables for monitoring and auditing purposes.Enhanced data quality and validation by integrating error-handling routines within data pipelines, reducing downstream reporting issues.Developed and maintained documentation for SQL procedures, pipeline workflows, and data models to support knowledge transfer and operational continuity.Involved in configuring Azure platform for data pipelines, ADF, Azure Blob Storage and Data Lakes and building workflows to automate data flow using ADFMigrated BI reporting tables and stored procedures from Azure SQL Database to Microsoft Fabric, refactoring logic for compatibility and performance within the Lakehouse architecture.Recreated Azure Data Factory (ADF) pipelines in Microsoft Fabric Data Pipelines, adapting orchestration logic and modifying SQL queries to align with Fabric’s execution context and Lakehouse structure.

Westminster International University in Tashkent

Bachelor's degree