Mridul Gupta

Background

About Mridul Gupta

With hands-on experience across the entire data lifecycle from ingesting and transforming data through ETL pipelines to storing it in cloud-based architectures. I specialize in converting raw data into actionable insights. My expertise bridges both data engineering and data science, allowing me to build scalable systems and extract meaningful analytical value. Currently working as a Data Engineer, I have practical experience with tools such as Databricks, Azure Data Factory, Azure Data Lake Storage (ADLS), Synapse, Delta Lake, Python, SQL, and PySpark. I focus on creating and optimizing ETL processes to ensure data consistency and quality, eliminate redundancy, and enhance runtime efficiency achieving up to a 60% reduction in execution time. My work spans across ETL orchestration, files ingestion, data movement and copy activities across multiple domains. Previously, I served as a Data Science Intern at Zummit Infolabs, where I spent over 8 months developing and fine-tuning machine learning and deep learning models. My projects included NLP tasks, audio-to-text conversion, and predictive analytics one of which involved an R&D initiative to build a speech-to-text system aimed at improving accessibility for deaf users. These efforts resulted in accuracy improvements of up to 20% in specific applications. Beyond work, I have a deep interest in astrophysics and actively participate in data exploration workshops. In my free time, I enjoy swimming, playing chess, and exploring computer games.