With a wealth of experience spanning over a decade in data engineering and MLOps, I bring a deep expertise in designing and implementing scalable data platforms and machine learning solutions. My journey has involved setting up extensive data infrastructure, including clusters of over 100 nodes and pipelines managing petabytes of data. My work with Fortune 500 companies has honed my skills in Databricks, Spark, and MLOps, allowing me to create and optimize data platforms that drive business intelligence and operational efficiency. My passion lies in unraveling complex data challenges and developing solutions that propel organizations forward. In my previous roles, I have contributed to groundbreaking projects and innovations. From leading data consultancy initiatives to co-authoring notable industry publications such as The Handbook of Data Science and AI, my career reflects a commitment to advancing data science and technology. My experience spans from developing key educational resources, including the "Complete dbt Bootcamp" on Udemy, to managing global data teams and consultancy projects. Each endeavor has enriched my understanding of the dynamic landscape of data engineering and reinforced my dedication to fostering a robust learning environment. As an instructor, I leverage my comprehensive background to provide valuable insights and practical knowledge in data engineering and machine learning. My teaching approach is grounded in real-world experience and a passion for solving data problems. Whether through direct training or innovative course development, I aim to equip learners with the skills and knowledge to excel in the evolving field of data science.