Rohan Sharma

I’m a data engineer with 3+ years of experience designing and optimizing scalable data pipelines. I focus on cloud-based ETL and data warehousing for analytics, using Databricks, Snowflake, and PySpark to drive reliable, high-performance data transformation.

At Tata Consultancy Services (Data Engineer – Kenvue / Johnson & Johnson Consumer Health), I led cloud migration for 100+ global retailers, transitioning legacy on-premise systems to cloud-native data processing and visualization. I implemented Databricks Unity Catalog and Apache Iceberg to establish governed data layers that reduced storage costs by 30% and eliminated data redundancy.

I architected unified ETL frameworks to consolidate disparate sources into a single cloud repository, improving accessibility for global analytics teams. I also built real-time monitoring dashboards and automated alerts, reducing system downtime by 40% through proactive failure detection.

To raise data quality and productivity, I integrated GenAI into data pipelines for automated data cleaning, schema mapping, and metadata generation. I’ve also leveraged LLMs to support natural language querying, auto-generate SQL, and deliver faster insights for non-technical users—while collaborating closely across cross-functional teams to keep data trustworthy.