Collaboration is at the heart of successful data engineering, and Git has become an essential tool for managing complex, multi-developer workflows. Yet many data practitioners are still getting up to speed with how to apply version control best practices in the context of data pipelines and analytics infrastructure. Mastering Git not only improves collaboration, but also ensures reproducibility, traceability, and long-term maintainability of data projects.
In this hands-on code-along, Amanda Crawford-Adamo, an experienced data engineer, walks you through collaborative data engineering practices using Git. You’ll learn how to manage data workflows with version control, explore advanced Git techniques like branching strategies and repository organization, and dive into a real-world case study about collaborating on a data pipeline. This session is perfect for data and software engineers looking to improve the way they build, share, and scale data infrastructure.
Key Takeaways:
- Learn best practices for collaborative data engineering using Git.
- Discover advanced Git techniques for managing shared repositories and resolving conflicts.
- Explore a real-world example of using Git to build a data pipeline as a team.
