I am a dedicated Data Engineer with a strong background in developing scalable data solutions and leveraging advanced machine learning techniques to drive business insights. My expertise lies in designing and implementing robust ETL pipelines, managing large-scale datasets, and optimizing data workflows using cutting-edge technologies.With hands-on experience in cloud platforms such as AWS, Google Cloud, and Azure, I have successfully led complex projects involving Apache Spark, PySpark, Databricks, and MongoDB, ensuring the seamless integration of data systems. My proficiency extends to building and deploying machine learning models, particularly in Natural Language Processing (NLP), recommendation engines, and neural networks, utilizing frameworks such as TensorFlow and Scikit-Learn.I have a proven track record of delivering high-impact data solutions, including the development of a Personalized Recommendation System and the deployment of scalable data pipelines in cloud environments. My technical expertise spans across Python, SQL, Snowflake, and advanced big data processing frameworks, complemented by my ability to automate and streamline data workflows using Docker, Airflow, and Jenkins.I hold a Master's degree in Computer Science from the University of North Carolina at Charlotte, where I specialized in Big Data Analytics, Machine Learning, and NLP. I am continuously seeking opportunities to apply my technical knowledge to solve real-world challenges and contribute to data-driven decision-making in dynamic environments.