• Primarily involved in Data Migration using SQL, SQL Azure, ADLS and Azure Data Factory• Build analytic tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics• Worked with Business team to build E2E pipelines to extract data and process.• Working with Source team to extract the data and it will be loaded in the ADLS• Involved in Design and Development of Ingestion Framework… Show more • Primarily involved in Data Migration using SQL, SQL Azure, ADLS and Azure Data Factory• Build analytic tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency and other key business performance metrics• Worked with Business team to build E2E pipelines to extract data and process.• Working with Source team to extract the data and it will be loaded in the ADLS• Involved in Design and Development of Ingestion Framework which is metadata driven. • Used Azure Databricks notebook to develop Facts and Dimension tables from extracted data in ADLS • Once it’s created pipelines and datasets will be triggered based on LOAD (History/Delta) operations• Based on source (big or small) data loaded files will be processed in Azure Databricks by applying operations in Spark SQL which will be deployed through Azure Data Factory pipelines• Involved in deploying the solutions to DEV, QA and PROD• Involved in setting up the environments for QA, DEV and PROD using DevOps• Professional in creating a data warehouse, design-related extraction, loading data functions, testing designs, data modeling, and ensure the smooth running of applications• Developed pipelines that can extract data from various sources and merge into single source datasets in ADLS using Databricks• Performed encryption of sensitive data into ADLS which are sensitive to business using cypher algorithm.• Decrypt the sensitive data using keys for refined datasets for analytics, by providing end users access• Created connections from different sources from On-prem and cloud to only source for Power BI reports• Coordinate with external teams to reduce data flow issues and unblock team members• Always actively participate in four ceremonies: Sprint planning meeting, Daily Scrum, Sprint review meeting, and Sprint retrospective meeting. Show less

• Design and developed pipelines to extract the data from Relational sources like Oracle, SQL Server, MySQL and non-relational sources like Flat files, JSON files using Azure Data Factory (ADF).• Developed Azure Databricks notebooks to apply the business logic transformations and perform data cleansing operations.• Built end-to-end metadata driven incremental loading pipeline using Azure Data Factory (ADF).• Developed data-flows for a code-free data transformation experience using… Show more • Design and developed pipelines to extract the data from Relational sources like Oracle, SQL Server, MySQL and non-relational sources like Flat files, JSON files using Azure Data Factory (ADF).• Developed Azure Databricks notebooks to apply the business logic transformations and perform data cleansing operations.• Built end-to-end metadata driven incremental loading pipeline using Azure Data Factory (ADF).• Developed data-flows for a code-free data transformation experience using Azure Synapse Workspace.• Built reusable pipelines in Data Factory to extract, transform and load data into Azure SQL DB.• Implemented SCD Type1, SCD Type2 logic using Azure Data Bricks for Delta tables.• Developed PySpark streaming applications and loaded them into bronze and silver, gold layers Using Azure Databricks.• Utilized version control systems such as Azure Devops Git and Github for efficient code repository management and collaborative development workflows. • Experience on Migrating data from SQL database to Azure Data Lake, Azure SQL Database using Azure Data factory. • Enhanced existing modules with new functionalities as per the user requirement.• Coordinating with other teams to get the required information to finish the work in time and to improve the process performance.• Resolving the production issues and modify the code to avoid issues in the future. Show less