Data engineering in the cloud demands scalability, flexibility, and real-time processing capabilities. Snowpark, a framework within the Snowflake ecosystem, empowers data engineers to efficiently build, scale, and manage data pipelines using popular programming languages such as Python, Java, and Scala. Snowpark's unique features, including its ability to push computation to Snowflake's engine, seamless integration with machine learning workflows, and its role in enabling real-time analytics. Benchmark comparisons, use cases, and analyses of cost-efficiency illustrate how Snowpark redefines data engineering in cloud-native ecosystems.