The modern data stack has improved upon previous tools, but it also introduces new problems such as fragmented observability, limited orchestration, and high cost. To solve these problems, a new role called the data platform engineer has emerged to manage complex data infrastructure. A good data platform should be scalable and maintainable, have high-quality governance and data observability and insights. It should also support software development lifecycle integration, heterogeneous use cases, declarative workflows, and different languages and tools. Code-based solutions are preferred over no-code or low-code for complex data engineering tasks, and Dagster can help build such a unified data platform with features like code locations and asset checks for data quality and governance. The role of the data platform engineer involves managing complex data infrastructure, building platforms that serve the needs of stakeholders, and moving from individual pipelines to frameworks and services that support the entire data ecosystem within an organization. Building a real data platform is more than just using modern data stack tools, it's thinking about scalability, governance, and observability. Dagster addresses these needs with features that tackle the challenges of today's data engineering.