Pranav Raghuwanshi

• Leading enterprise-wide data engineering efforts using Azure Data Factory, Databricks, and Data Lake architecture.
• Architecting data modeling solutions for BI and analytics teams, enabling scalable and governed semantic layers.
• Developing Generative AI applications in enterprise settings to bridge traditional data systems with intelligent agents.
• Building semantic search solutions involving Retrieval-Augmented Generation (RAG), LangChain, and Azure OpenAI which have capabilities to perform semantic search on videos, different file formats and images.
• Developing intelligent data agents to interact with structured systems and semantic layers to create an alternative for traditional reporting.
• Investigating LLMOps best practices and governance models in Azure ecosystems.
• Acting as Microsoft Fabric Administrator, overseeing workspace governance, data security, and Fabric workloads.

• Leading enterprise-wide data engineering efforts using Azure Data Factory, Databricks, and Data Lake architecture.
• Architecting data modeling solutions for BI and analytics teams, enabling scalable and governed semantic layers.
• Delivered high-performance ETL pipelines and data warehouses across industries.
• Implemented Delta Lake architecture for scalable, reliable data availability.
• Worked extensively on hybrid BI solutions integrating legacy systems with modern cloud data platforms.
• Supported enterprise transitions to cloud-native data engineering and governance solutions.

• Develop, Test and Deploy Azure data factory pipelines and logic apps on DEV, TEST and PROD based on requirement or change request.
• Ingesting data in Data lake, Delta lake (bronze, silver, gold) and azure blob storage.
• Collaborated with cross-functional teams to achieve project goals on time and within budget.
• Improved customer satisfaction rates through proactive problem-solving and efficient complaint resolution.

• Developed SSIS and Pentaho packages for the Dev and then
  deploy them to higher env.ironment.
• Doing the unit and performance testing as well have a
  communication with the client for the requirement
  gathering.
• Production Support of live and business critical applications