Deploying Data Models with Confidence: A CI/CD Approach in Data Engineering

Description

We often rave about the latest data engineering tools - modern warehouses, transformation frameworks, and orchestration platforms but we rarely talk about how these models get deployed with confidence. CI/CD (Continuous Integration & Continuous Deployment) is often seen as a software development practice, but in reality, it plays a game-changing role in data engineering. Without CI/CD, data teams face manual deployments, broken pipelines, and inconsistent data models, leading to unreliable insights.

Abstract

In this session, we'll explore how CI/CD can revolutionize data model deployment by bringing automation, version control, and testing into the process. Using SQLMesh, Snowflake, Apache Iceberg, and GitHub Actions, we'll walk through building a robust, automated data workflow from development to production. From ensuring transformations are validated early to managing code and data versions seamlessly, this talk provides actionable guidance for building reliable pipelines at scale. By the end of this session, you'll learn how to: - Integrate CI/CD pipelines into data workflows using GitHub Actions for automated deployments. - Set up validation and testing for SQLMesh models to catch issues before they reach production. - Use Snowflake and Apache Iceberg to manage scalable, versioned datasets with confidence. - Improve pipeline reliability by eliminating manual steps and promoting consistency across environments. Whether you're a data engineer, analytics engineer, or platform builder, this talk will show why CI/CD is no longer optional but essential for modern, trustworthy data workflows.

Key Takeaways

• Integrate CI/CD pipelines into data workflows using GitHub Actions for automated deployments
• Set up validation and testing for SQLMesh models to catch issues before they reach production
• Use Snowflake and Apache Iceberg to manage scalable, versioned datasets with confidence
• Improve pipeline reliability by eliminating manual steps and promoting consistency across environments