Dimple Wadhwa
Azure Data Engineer @Verifone
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WORK HISTORY
Azure Data Engineer @Verifone
Involved in the design and deployment of data ingestion pipelines with Azure Databricks, facilitating real-time data processing and analytics to support immediate data availability for downstream applications• Engineered scalable and high-performance data warehousing solutions using Azure Synapse Analytics, optimizing for data storage architectures that enhance analytics capabilities• Crafted dimensional data models and orchestrated ETL processes through Azure Data Factory, integrating and loading data into Azure Synapse Analytics to maintain data consistency and integrity• Employed Azure Stream Analytics for instant analytics on streaming data, deriving actionable insights to respond swiftly to critical events and trends• Developed comprehensive data integration solutions with Azure Data Factory, automating data workflows to ensure seamless exchange between on-premises and cloud environments, and enhancing interoperability• Utilized Azure Purview for automated data scanning and classification across Azure platforms, facilitating robust data governance, discovery, and compliance with regulations• Directed the transition of on-premises data warehouses to Snowflake, leading the design and optimization efforts that culminated in reduced query times and cost savings through efficient resource management• Created and managed ETL pipelines integrating Azure Data Lake, ensuring the consolidation of diverse data sources into a unified repository, supporting scalable, secure, and reliable data storage and analytics• Enabled the integration of varied data sets into cohesive models using Azure Data Factory and Azure Data Lake, supporting comprehensive BI and analytical frameworks• Achieved a 30% reduction in infrastructure costs and enhanced data processing speeds by developing a scalable data architecture on the Azure cloud platform
EDUCATION
Conestoga College
Post- Graduate Certificate
Medicaps Institute Of Technology and Management
Bachelor of Engineering
ABOUT DIMPLE WADHWA
Highly skilled Azure Data Engineer with nearly 4 years of experience in the IT sector, focusing on Data Engineering and Data Integration practices • Proficient in leveraging Azure services such as Azure Data Factory, Azure Event Hubs, and Azure IoT Hub for efficient and scalable data ingestion from various sources, including databases, streaming platforms, and IoT devices • Skilled in designing and implementing data storage solutions on Azure, including Azure SQL Database, Azure Cosmos DB, Azure Blob Storage, and Azure Data Lake Storage, to meet diverse data storage and retrieval needs • Experienced in designing and implementing data warehousing solutions on Azure using Azure Synapse Analytics and Azure SQL Data Warehouse to enable fast and efficient querying of large-scale datasets for business intelligence • Proficient in implementing data processing pipelines on Azure using services such as Azure Databricks, Azure HDInsight, and Azure Data Lake Analytics for batch and stream processing of big data workloads • Experienced in architecting and optimizing data warehousing solutions on Snowflake, leveraging its unique multi-cluster architecture and cloud-native features to deliver scalable, high-performance analytics platforms for data-driven organizations • Skilled in integrating data from disparate sources and systems using Azure Data Factory, Azure Logic Apps, and Azure Functions to create a unified view of data across the organization • Proficient in implementing data catalog solutions on Azure using Azure Purview to create a centralized metadata repository that provides a comprehensive inventory of data assets, data lineage, and data quality metrics • Experienced in designing and orchestrating ETL (Extract, Transform, Load) processes on Azure using Azure Data Factory, Azure Databricks, and Azure SQL Database to move, transform, and load data between various data sources and destinations with 99% accuracy • Skilled in setting up and managing CI/CD pipelines, facilitating streamlined data deployments which contribute to quicker insights and improved decision-making processes. • Experienced in agile project environments, understanding agile methodologies and Lean practices, contributing to efficient project execution and management.
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