My name is Yashodhan Jaltare. I am a master’s student at the University of North Carolina at Charlotte, majoring in Computer Science with a concentration in Data Science.

I am a passionate data engineer and machine learning practitioner with a strong foundation in building high-performance ETL pipelines, optimizing large-scale databases, and implementing ML models for impactful real-world applications. I bring both academic expertise and hands-on experience from roles in industry-leading companies and ambitious projects.

Data Engineering: With extensive experience in designing and optimizing ETL pipelines on platforms like Databricks, Azure Data Warehouse, and SQL Server, I’ve successfully managed and processed databases of over 80 million records, reducing loan processing times and enhancing risk management. My work with T-SQL, Hadoop, and other big data tools has allowed me to deliver robust data solutions that drive business growth and efficiency.

Machine Learning: My ML expertise spans from traditional algorithms to neural networks and NLP, using frameworks like TensorFlow, PyTorch, and Scikit-Learn. Projects such as building a question generation app using Qwen2.5 LLM and a movie recommender showcase my skill in applying cutting-edge techniques for customized solutions. I focus on model optimization, efficient data pipelines, and generating actionable insights that support decision-making.

DevOps: Skilled in DevOps tools like Azure DevOps, Docker, and Kubernetes, I’ve architected CI/CD pipelines that improve code management, security, and delivery timelines. By integrating these practices into data engineering workflows, I aim to streamline deployments and support dynamic, scalable infrastructure.