Rishab Aggarwal

Worked extensively with Spark to implement complex data transformations, aggregations, and schema validations across distributed datasets. Led a data engineering team for clinical data reporting platform using Databricks, Azure Data Lake, Azure Data Factory designing end-to-end ETL pipelines in an Agile setup. Built Python and R analytical workflows, creating interactive Plotly visualizations for real time insights. Orchestrated Databricks Jobs via REST APIs to run dataset sanity check notebooks, reducing pipeline failures by 35% and optimizing ADLS storage. Built an API-based caching system using Azure MySQL and Data Lake, eliminating redundant runs and reducing Spark cluster costs by 40%, enabling instant report rendering. Collaborated with consultants and stakeholders to deliver Power BI dashboards and CI reports translating business needs into actionable insights. Developed and integrated REST APIs using Express.js for a internal reporting web application. Collaborated with data scientists to implement LLMs for text mining and building classification models. Leveraged Excel, SQL, and Power BI to analyze sales and launch data, generating data-driven trend-based insights that gui

Leveraged Excel based analytics and forecasting to support pricing and marketing strategies for Wyndham and Choice Hotels, achieving a 40% peak-season revenue uplift and 20% monthly growth. Communicated forecasting insights and performance reports to major stakeholders, enabling data-driven pricing and marketing decisions.