Dhrumil Patel Email & Phone Number

Jacksonville, Florida, United States

• Integrated data from various on-premises and cloud sources into Azure Data Lake, improving data accessibility and scalability.
• Migrated legacy data to Snowflake using DBT within Azure, enhancing performance and reducing query latency.
• Leveraged Azure Databricks to perform ETL processes, optimizing data transformation and reducing processing time by 30%.
• Developed and maintained data pipelines using Azure Data Factory, ensuring seamless data flow between systems.
• Optimized Azure SQL Database performance through indexing and query tuning, reducing query execution time by 40%.
• Conducted comprehensive data validation and cleansing, resulting in a 98% accuracy rate in the final datasets.

Tampa, Florida, United States

• Architected and managed an Azure SQL Data Warehouse, improving data retrieval speed and storage efficiency.
• Integrated diverse data sources into Azure Data Lake, providing a unified platform for data analysis.
• Integrated data from multiple sources, resulting in a unified data warehouse that supported comprehensive business analysis.
• Utilized Azure Databricks to process and analyze large datasets, reducing data processing times by 40%.
• Developed complex ETL workflows in Azure Data Factory, streamlining data ingestion and transformation processes.
• Tuned SQL queries in Azure SQL Database, improving performance by 35% and reducing resource consumption.

Cleveland, Ohio, United States

• Designed and implemented data workflows in Azure Data Factory to automate data extraction and transformation tasks.
• Integrated marketing and sales data into Azure Data Lake, providing a centralized repository for analytics.
• Integrated SAS analytics with Azure environments, enhancing the capability to analyze large datasets.
• Employed Azure Databricks for data processing tasks, optimizing performance and enabling scalable data analysis.
• Automated ETL processes using Azure Data Factory, reducing manual data handling and improving efficiency by 50%.
• Consolidated data from multiple sources, harmonizing datasets for improved consistency and reliability.