Jivitesh Arora

• Designed and implemented data ingestion pipelines using Azure Data Factory to extract, transform, and load (ETL) data from various sources into Azure Blob storage and Azure Data Lake Storage
• Developed and maintained data processing workflows using Azure Databricks and PySpark to handle large-scale data transformations and analytics tasks efficiently
• Created and managed data catalogs using Azure Data Catalog to enable easy discovery and collaboration on data assets across the organization
• Implemented data security and access controls for Azure SQL Database and Azure Cosmos DB to ensure compliance with regulatory requirements
• Conducted performance monitoring and tuning of Snowflake data warehouses, including workload management, query optimization, and resource scaling, to achieve optimal performance and cost-effectiveness
• Orchestrated end-to-end ETL pipelines using PySpark and Snowflake to extract data from various sources, transform it according to business logic, and load it into data warehouse
• Utilized Azure Synapse Analytics for building and optimizing data warehousing solutions, including data modeling, partitioning, and indexing for improved query performance
• Collaborated with stakeholders to gather requirements and design scalable data architectures for supporting business intelligence and reporting needs in Power BI
• Automated data integration processes and workflows using Python scripts and Azure Data Factory pipelines to improve operational efficiency and reduce manual effort
• Monitored and optimized data pipelines and storage solutions using Azure Monitor, ensuring high availability, performance, and reliability of data services

Designed and implemented data ingestion pipelines using Azure Data Factory to extract, transform, and load (ETL) data from various sources into Azure Blob storage and Azure Data Lake Storage
Developed and maintained data processing workflows using Azure Databricks and PySpark to handle large-scale data transformations and analytics tasks efficiently
Created and managed data catalogs using Azure Data Catalog to enable easy discovery and collaboration on data assets across the organization
Implemented data security and access controls for Azure SQL Database and Azure Cosmos DB to ensure compliance with regulatory requirements
Conducted performance monitoring and tuning of Snowflake data warehouses, including workload management, query optimization, and resource scaling, to achieve optimal performance and cost-effectiveness
Orchestrated end-to-end ETL pipelines using PySpark and Snowflake to extract data from various sources, transform it according to business logic, and load it into data warehouse
Utilized Azure Synapse Analytics for building and optimizing data warehousing solutions, including data modeling, partitioning, and indexing for improved query performance
Collaborated with stakeholders to gather requirements and design scalable data architectures for supporting business intelligence and reporting needs in Power BI
Automated data integration processes and workflows using Python scripts and Azure Data Factory pipelines to improve operational efficiency and reduce manual effort
Monitored and optimized data pipelines and storage solutions using Azure Monitor, ensuring high availability, performance, and reliability of data services