Jivitesh Arora Email & Phone Number

• Highly motivated Azure Data Engineer with 1 year of experience designing, developing, and deploying data pipelines and data warehousing solutions on the Microsoft Azure platform• Proven ability to leverage Azure services like Data Factory, Databricks, Synapse, and Storage solutions to build scalable and efficient data architectures• Possess in-depth knowledge of Azure Data Factory (ADF) for orchestrating complex data workflows, Azure Databricks for advanced data processing with PySpark, and Azure Synapse Analytics for unified data warehousing and analytics• Skilled in designing and implementing data models for efficient data storage and retrieval, Utilize ETL/ELT processes to seamlessly move data between diverse sources and destinations• Dynamic in highly scalable data model and data warehouse using Snowflake, resulting in a 40% improvement in data processing speed and a 25% reduction in storage costs• Leverage Azure Data Lake Storage (ADLS) for scalable data lakes, Azure Blob Storage for unstructured data management, and Azure SQL Database for relational data storage, ensuring secure and reliable data access• Adept at utilizing Azure Stream Analytics to process and analyze real-time data streams to extract valuable insights from continuous data streams, enhancing operational efficiency and responsiveness• Understand the importance of data governance to register, curate, and manage data assets effectively, ensuring data quality, compliance, and accessibility • Implement Proactive data monitoring practices to ensure data pipeline health and identify potential issues, minimizing downtime and optimizing data processing efficiency• Possess strong programming skills in Python and PySpark to manipulate and analyze data efficiently, enabling streamlined data processing workflows and advanced analytics capabilities• Successfully migrated data from various sources to target platforms, ensuring data integrity and continuity, and consistency and deliver migration projects within scope, budget, and timeline constraints• Thrive in collaborative environments, effectively communicating technical concepts and working seamlessly with data analysts, scientists, and developers• Good in integrating Jira with Confluence to synchronize project tasks and documentation seamlessly, enabling stakeholders to access up-to-date information and track project milestones effectively

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  Trent University

  Computer Science