Rahul M

WORK HISTORY

ABOUT RAHUL M

Around 5 years of experience in Data Analysis, Data Engineering in Commercial, Financial, Retail and Health domains, Data wrangling, Data Scrubbing, Implementing ETL processes and Orchestrating, Data visualization to draw meaningful insights, Data Warehousing, Cloud. • Experience in writing SQL queries to obtain filtered data for RDBMS such as SQL Server, MySQL, PostgreSQL, and Oracle, MySQL databases such as Mongo DB and Cassandra to handle unstructured data. • Extensive experience in Azure Cloud, Azure Data Factory, Azure Data Lake Storage, Azure Synapse Analytics, Azure Analytical services, Azure Cosmos NO SQL DB, Azure HDInsight, and Data bricks. • Experience in Migrating SQL database to Azure Data Lake, Azure Data Lake Analytics, Azure SQL Database, Data Bricks, and Azure SQL Data warehouse, Controlling and granting database access, and Migrating On-premises database to Azure Data Lake store using Azure Data factory. • Experienced with Dimensional modelling, Data migration, Data cleansing, Data profiling, and ETL Processes features for data warehouses • Experience in writing SQL queries to obtain filtered data for RDBMS such as SQL Server, MySQL, PostgreSQL, and Oracle, MySQL databases such as Mongo DB and Cassandra to handle unstructured data. • Extensive experience in Azure Cloud, Azure Data Factory, Azure Data Lake Storage, Azure Synapse Analytics, Azure Analytical services, Azure Cosmos NO SQL DB, Azure HDInsight, and Data bricks. • Experience in Migrating SQL database to Azure Data Lake, Azure Data Lake Analytics, Azure SQL Database, Data Bricks, and Azure SQL Data warehouse, Controlling and granting database access, and Migrating On-premises database to Azure Data Lake store using Azure Data factory • Hands-on experience on MS Azure Cloud suite: Azure SQL Database, Azure Data Lake (ADL), Azure Data Factory (ADF), Azure SQL Data Warehouse, Azure Service Bus, Azure Key Vault, Azure Analysis Service(AAS), Azure Blob Storage, Azure Search, Azure App Service, and Azure Data Platform Services. • Ability to develop ETL pipelines in and out of data warehouse using combination of Python and Snowflake\'s Snow SQL. • Proficient in Data Modeling Techniques using Star Schema, Snowflake Schema, Fact and Dimension tables, RDBMS, Physical and Logical data modeling for Data Warehouse and Data Mart. • Experienced with Dimensional modelling, Data migration, Data cleansing, Data profiling, and ETL Processes features for data warehouses. • Used Airflow to schedule, manage and monitor Spark Jobs on a Cluster