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Collaborative Data Modeling in VS Code — Bridging Modelers and Engineers through Metadata
A modern metadata-driven development workflow where data modelers define logic and semantics declaratively, while data engineers operationalize these definitions in SQL and Jinja macros. Powered by VS Code, JSON validation, and language-server intelligence, this approach unites modeling and engineering into a single semantic DevOps loop.
Summary
Treat models as code.
Data modelers express business meaning, structure, and mappings in YAML; data engineers build reusable macros and SQL templates that translate these definitions into executable code.
Both collaborate in VS Code with language-server support, automated diagram generation (ERD, Mapping, Data Flow), and Copilot assistance. Logical and physical models coexist in one repository, validated by JSON Schemas and connected through shared metadata.
1. A New Division of Labor
Modern data teams thrive when modelers and engineers work in parallel, not in sequence.
The modeler defines the intent — what data means and how it should relate.
The engineer defines the mechanism — how those semantics become performant, maintainable SQL.
