Rohan Gawal

WORK HISTORY

EDUCATION

ABOUT ROHAN GAWAL

As a skilled Data Engineer with 4+ years of hands-on experience in the healthcare and insurance domains, I specialize in designing and implementing scalable data pipelines to streamline data ingestion, processing, and analysis. My work focuses on optimizing data workflows and enabling actionable insights that enhance organizational revenue and operational efficiency. In my recent project, I led the development of an end-to-end data pipeline for a U.S-based healthcare client, enabling the seamless ingestion of 10–20 GB of daily data from multiple sources, including MySQL databases and FTP file servers (CSV, XML, JSON formats). Using Apache NiFi, HDFS, and Hive for ingestion and storage, I built robust ETL pipelines with PySpark to perform schema validation, deduplication, type enforcement, and business rule checks—ensuring high-quality datasets for downstream analytics and reporting. I also implemented the Medallion Architecture (Bronze → Silver → Gold) to layer and enrich the data systematically, with the Silver layer handling advanced validation (referential integrity, uniqueness, null checks) and the Gold layer used for aggregations and business KPIs. The solution was deployed on AWS using services such as EMR, S3, and Glue, and orchestrated using Apache Airflow. Technical Stack: Apache NiFi | Apache Spark & PySpark | Hadoop Ecosystem (HDFS, Hive)| AWS (EMR, S3, Glue, Athena, Redshift)| Apache Airflow | MySQL | Parquet | JSON/XML/CSV | SQL | Linux I am passionate about building reliable, scalable, and performance-optimized data platforms that empower businesses to make data-driven decisions. Always eager to take on new challenges and learn emerging technologies in the data engineering space.