Umang Sethi

Experience

• 

  Navika Capital Group Llc

  May 2019 - Aug 2019

  Information Technology Intern

  Worked with the IT team to develop a data management website that collects data daily from 500+ hotel properties across the country. This project had a major impact on the information management had about their properties. With the help of mySQl and other tools we were able to make a unified system for a major real estate company

• 

  Pyle

  May 2020 - Sept 2020

  Software Engineer Intern

  Worked under the CTO of the startup, using Django framework to build a web application for a financial technology startup. Worked on creating different web pages and linking them together and implementing a login system for web application.

• 

  Kappa Sigma Fraternity

  May 2021 - Jul 2022

  Philanthropy Chair

  Plan and Delegate events to raise money and awareness for various charities. Partnered with Suffolk Highway Association to adopt a highway and managed monthly cleanups.

• 

  The Estée Lauder Companies Inc.

  Jun 2021 - May 2022

  Worked on Data and Analytics team to implement row security on Enterprise Data Lake for various brands and functions. Utilizing tools like Azure Data Factory, Microsoft Master Data Services and SQL. Successfully developed on Enterprise Data Lake to create a more reliable and stable process to handle data using RESTful APIs. Created pipelines to create secure flow of data. Got exposure to Agile methodology, Software Development Life Cycle, Azure Data Factory, Databricks, PySpark and PowerBI.

  • Big Data Engineer Apprentice

    Sept 2021 - May 2022

  • IT Data and Analytics Intern

    Jun 2021 - Aug 2021
• 

  The Estée Lauder Companies Inc.

  Jul 2022 - now

  * Architected Data Mesh Nodes in partnership with solution architects, standardizing frameworks across Azure Data Factory, Databricks, and orchestration tools to improve data sharing, eliminate silos, and enhance decision-making through seamless integration.* Designed a modular ingestion framework in collaboration with vendors, streamlining deployment, enhancing scalability, and increasing operational efficiency across new nodes.* Designed and implemented security for SQL warehouses connected to Power BI, configuring AD groups to create a user-friendly architecture, enhancing data security while minimizing the need for backend technical knowledge for end users.* Implemented liquid clustering techniques to optimize Power BI performance with Databricks, significantly improving query efficiency and data retrieval. Delivered a responsive reporting environment, driving substantial improvements in user experience and data performance.* Migrated project management and documentation processes to Jira and Confluence, optimizing team workflows, improving collaboration, and ensuring documentation is well-organized, accessible, and consistently updated.* Delivered robust data engineering solutions using Azure Data Factory and PySpark, streamlining workflows and enabling scalable, efficient data provisioning to ensure seamless access to accurate, timely information for critical business operations. Show less * Led the transition from schedule-based to event-driven reporting on Power BI, automating report generation using an internal orchestration tool to eliminate manual intervention and ensure real-time data refreshes for improved efficiency.* Managed Azure cloud infrastructure and Databricks workspaces, implementing ACLs for secure storage access and organizing workspaces for optimized resource allocation and efficient pipeline execution.* Developed custom PySpark scripts for data engineering needs, enabling ad hoc functionalities and specialized reporting to enhance workflow efficiency and address unique data processing requirements.* Served as a tech lead for migrating from Netezza to Databricks, implementing the prepared layer and transitioning from MicroStrategy to Power BI, reducing costs and proving the scalability of the new architecture.* Modernized infrastructure by collaborating with solution architects to implement a data mesh strategy, improving data sharing and scalability while leading the migration of the prepared layer from SQL Server to Databricks, implementing SQL warehouses, and upgrading Databricks clusters. Show less

  • Senior Cloud Data Engineer

    Jul 2024 - now

  • Cloud Data Engineer

    Jul 2022 - Jul 2024