Chirag Gorsia

• 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.

• Analyzed large datasets to identify trends and patterns in customer behaviors.
• Leveraged advanced analytics tools to create interactive dashboards that provided actionable insights into key business metrics.
• Optimized data pipelines by implementing advanced ETL processes and streamlining data flow.

• Worked as individual contributor on bigdata technologies like Databricks.
• Worked on building spark recommendation engine that gave recommendation on small file issue, spill to disk, data skewness etc.
• Worked on dangerous goods project migration from on-premise data to azure using Datafactory and Databricks.

• Managed 3 teams of 5,4,3 people each.
• Enabled team for timely delivery of project requirements.
• Mentored team on latest technology by conducting trainings and guiding them on work automation.

• Managed a team of 3 members.
• Worked and managed a data migration project.
• Worked on data migration from Oracle On-premise database to Postgres database on AWS.

• Managed a team of 4 members.
• Worked on Teradata database with one in the leading retail giants form New-Zealand.

• Worked of building data for “targeted interaction”.
• Developing Teradata scripts to load and transform data.

• Worked on various client facing projects.
• Developing data pipelines using technologies like Teradata, Informatica.