An enthusiastic and determined Cloud Data Engineer/Lead BI Programmer with creative flair of 15+ years of experience and specialized in managing dev teams, developing and migrating BI solutions, data warehouse, data stores with a strong emphasis on distributed ETL & Azure Cloud ETL Frameworks.SUMMARY OF QUALIFICATIONS• A competent Azure Data/Synapse DWH/Fabric lead with 15 years of experience in IT, with strong capabilities to provide high quality cloud/data/BI/ETL solutions, data strategies, and architecture across various technology landscapes, helping organizations maximize their utilization of existing data investments.• Delivered several Data Strategy Implementations across several client verticals that is high in performance throughput/ data availability, time and cost efficient and scalable.• Proficiency in Data Transformations, Data Governance, Data Management and Data Visualization using various Data Tools and frameworks.• Represented as a dependable Liaison between Business Stakeholders and IT members to help deliver many BI projects.• Building Modern data solutions using Azure PaaS service to support visualization of data. Understand current Production state of application and determine the impact of new implementation on existing business processes.• Extract Transform and Load data from Sources Systems to Azure Data Storage services using a combination of Azure Data Factory ,T-SQL, Spark SQL and U-SQL Azure Data Lake Analytics. Data Ingestion to one or more Azure Services - (Azure Data Lake,• Azure Storage, Azure SQL, Azure DW) and processing the data in In Azure Data bricks.• Created Pipelines in ADF using Linked Services/Datasets/Pipeline/ to Extract, Transform and load data from different sources like Azure SQL, Blob storage, Azure SQL Data warehouse, write-back tool and backwards.• Setup the Delta Lake within Azure Databricks to write only the delta records into the Refined folder of the ESR Data Lake & Setup & schedules several Master / Child Azure Databricks Notebooks.• Experience in handling huge databases ranging from 100 GB to 10 TB.• Involved in DBA activities likes I/O distribution Analysis, SQL Server Resource Wait Stats Analysis, Index Analysis, TempDB Space complexity, Fragmentations and Defragmentation, DBCC Best Practices.• Capable of processing large data using Cloud ecosystem and Big Data Analytics, which includes performing source-to-target data mapping, design and review.• Build OLAP cubes for multi-dimensional analytics directly on Hadoop with linear scalability