• Developed and maintained scalable ETL pipelines using SSIS, Azure Data Factory, and Databricks, processing millions of records daily.• Applied software architecture principles in designing scalable, maintainable ETL pipelines, following best practices for performance optimization and futureproofing.• Automated file transfer processes using Move It MFT, improving data availability and reducing manual effort by 40%.• Coordinated with cross-functional teams to optimize data ingest and egress processes, improving pipeline efficiency by 25%.• Implemented CI/CD pipelines using Azure DevOps, automating deployments and ensuring continuous integration of data workflows.• Performed complex data transformations for client-specific datasets, enhancing data quality and increasing reliability by 20%.• Automated disenrollment processes for client projects, handling sensitive data with accuracy, resulting in a 15% improvement in operational efficiency.• Managed project tasks using JIRA, improving project tracking by 20%.

 Developed end-to-end data engineering solution using Microsoft Fabric, processing 10+ TB of global sales data through bronze, silver and gold layers of the Medallion Architecture, reducing latency by 25% and improving data quality and accessibility by 40%.  Developed scalable ETL pipelines using Azure Data Factory, Databricks, and PySpark automating data ingestion and processing across multiple layers, reducing manual intervention by 90%.  Implemented Python and Spark in Azure Databricks to create scalable ETL pipelines, processing structured and unstructured data from multiple APIs, reducing processing time by 25%.  Implemented advanced data transformation and enrichment processes in Databricks, including UDFs for reverse geocoding, enhancing data usability for BI reporting by 35%.  Utilized Delta Lake technology in Microsoft Fabric Lakehouse for eAicient data versioning and transactional capabilities, improving data integrity by 20%.  Designed and deployed 10+ Power BI dashboards using direct lake querying for real-time KPI tracking, reducing operational costs by 15% through actionable insights.  Developed 15+ complex DAX measures and calculations in Power BI, improving stakeholder data accessibility by 25% and decision-making eAiciency by 30%.  Implemented Row-Level Security (RLS) using Azure Active Directory, enhancing data governance and security across Power BI reports by 20%.  Integrated Power Apps with Power BI for real-time data insights, embedding key metrics directly into business workflows.  Leveraged Power Automate to streamline data uploads and notifications, reducing manual effort by 40% and ensuring real-time data updates.  Performed data validation, error checking, and performance tuning, improving report reliability by 20% and reducing query run time by 15%.

 Migrated 10+ TB of on-premises data into Azure Data Lake using Azure Data Factory (ADF) and Databricks, reducing data latency by 25%.  Designed and developed scalable ETL pipelines using ADF and PySpark, processing millions of records daily and improving ETL speed by 20%.  Transformed raw data into bronze, silver, and gold layers in Databricks, improving data accessibility by 30%.  Integrated REST APIs for external data ingestion into Azure, ensuring seamless data flow and real-time data availability.  Enhanced data governance and security through Row-Level Security (RLS) and Azure Active Directory.  Reduced ETL pipeline execution time by 20% through performance tuning and data partitioning strategies.  Developed 10+ real-time Power BI dashboards to track key KPIs, reducing operational costs by 15% through actionable insights.  Automated Power BI data refresh schedules, ensuring timely updates from the gold data layer and enhancing decision-making.  Used ServiceNow for ticket management and collaboration with cross-functional teams, improving support response time by 20%.

 Interacted with Business Analysts and stake holders to gather businessrequirements. Developed ETL jobs like data transformation using Microsoft SQL ServerIntegration Services. Transferred data from various data sources/business systems including DB2,MS Excel, MS Access, Flat Files etc. to SQL Server using SSIS packages andother features like Excel source, Flat file source, transformation etc. Createdderived column from the present columns for the given requirements. Created SSIS packages, staged data from different data sources, consolidatedand merged into one single source. Designed and implemented relational databases, data marts and developedreports to allow users to easily access data. Developed reports with consistent drill-down functionality using Drilldownreport and Summary Report. Used SSRS to create, execute, and deliver tabular, matrix, and charts reports.