• Results-driven Data Engineer with expertise in designing and implementing scalable data ingestion pipelines using Azure Data Factory.• Proficient in utilizing Azure Databricks and Spark for distributed data processing and transformations.• Extensive experience in leveraging Azure services such as Azure Blob Storage, Azure SQL Database, and Azure Data Lake Storage for storing and managing data within the Azure ecosystem.• Hands-on expertise in utilizing Azure Stream Analytics for real-time data processing and integration with Azure Event Hubs for handling high-throughput, real-time data streams.• Proficient in utilizing Azure Monitor and Azure Log Analytics for monitoring and managing the performance of data pipelines, proactively identifying and addressing potential issues.• Strong proficiency in optimizing Spark jobs and utilizing Azure Synapse Analytics for processing and analyzing large-scale data.• Good experience in Spark Architecture including Spark Core, Spark SQL, Data Frames, Spark Streaming, Driver Node, Worker Node, Stages, Executors.• Proficient in implementing Role-Based Access Control (RBAC) for managing user access to Azure data resources.• Experience with Active Directory integration for user authentication and authorization within Azure.• Skilled in securing sensitive information like passwords, certificates, and API keys using Azure Key Vault.• Skilled in designing cloud-based data warehouse solutions using Snowflake on Azure, optimizing schemas, tables, and views for enhanced data storage and retrieval efficiency.• Demonstrated knowledge and comprehension of Snowflake cloud technology.• Practical experience utilizing Snowflake Clone and Time Travel functionalities.• Actively involved in enhancing, maintaining, and developing Snowflake database applications.• Establishing roles and determining necessary privileges for accessing various database objects.• Collaboratively implement appropriate data models and structures by working with data analysts and stakeholders.• Demonstrated history of success in optimizing performance and conducting capacity planning to ensure scalability and efficiency.• Expertise in creating CI/CD frameworks for data pipelines and collaborating with DevOps teams to automate pipeline deployment processes.• Proficient in scripting languages such as Python and Scala.• Possess expertise in utilizing Hive, Spark SQL, Kafka, and Spark Streaming for ETL tasks and real-time data processing.