- Developed and optimized T-SQL scripts, including stored procedures and validation scripts, to ensure data integrity and performance.- Designed and managed Azure Data Factory (ADF) pipelines to automate ETL processes and migrate data from SQL Server to Azure SQL Database.- Migrated on-premises data to Azure Data Lake Store (ADLS) and integrated various data types using ADF.- Combined structured, semi-structured, and unstructured data (e.g., log files, media) into Azure Blob Storage using ADF pipelines.- Utilized AWS Glue for ETL workflows, custom Python and PySpark scripts, and managed big data processing with AWS EMR, leveraging Hadoop, Spark, and Hive.- Developed data warehouse process models, including data sourcing, loading, transformation, and extraction.- Designed and implemented star and snowflake schema data models for efficient data warehousing solutions.- Created and scheduled stored procedures in the Azure environment to automate data processing tasks- Implemented Power BI semantic models and visualizations, including parameterized reports, charts, graphs, and drill-down reports, to support business data analysis.- Loaded and analyzed data from Azure Synapse Data Warehouse to provide actionable insights.- Deployed and tested code using Visual Studio Team Services (VSTS), ensuring robust CI/CD pipelines.- Automated ETL processes using SSIS and Azure Data Factory, including package creation and modifications for various data operations.- Implemented CI/CD practices with Jenkins, Azure DevOps, and GitLab CI/CD, automating builds, tests, and deployments. - Prepared source-to-target and data mapping documents to establish relationships and transformations between source and target systems. - Collaborated with subject matter experts to understand business requirements and create effective data migration strategies. - Proficient in using Snowflake for data warehousing, including performance optimization and ETL pipeline development.

ETL Development:-Designed and developed ETL workflows using Azure Data Factory, incorporating custom activities and complex data transformations. - Leveraged Databricks for advanced data processing and pipeline creation using Python and PySpark, improving data integration and analysis.- Created and deployed SSIS packages for extracting, transforming, and loading data from diverse sources such as flat files, CSV, and Excel.Database Management:- Engineered complex T-SQL code, including stored procedures, functions, triggers, and views, to support application functionalities and business processes. - Employed indexing strategies and query optimization techniques to enhance database performance and ensure efficient data retrieval.- Developed and maintained temporary tables and table variables to simplify complex queries and improve overall query performance.- Created and managed SSIS packages, including implementing error handling and logging mechanisms to track package execution and address issues effectively.Business Intelligence:- Designed and implemented Power BI visualizations and interactive dashboards, providing actionable insights based on business requirements and data analysis.- Created parameterized, cross-tab, and drill-down reports using SSRS to support decision-making and operational reporting needs.- Managed data extraction, transformation, and loading processes for SSAS cubes, ensuring accurate and timely data for analytical purposes.CI/CD and Automation:- Implemented CI/CD pipelines using Jenkins, Azure DevOps, and GitLab CI/CD.- Scheduled and managed automated SSIS package executions with SQL Server Agent and JAMS.Data Warehousing:- Designed high-level ETL architecture for data transfer from OLTP systems to data warehouses, optimizing data flow and storage efficiency.- Normalized database tables, enforced data integrity, and created secure views.- Built and processed fact and dimension tables with complex transforms.