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Collaborative Data Engineering with Git

Amanda Crawford-Adamo, an experienced data engineer, walks you through collaborative data engineering practices using Git.
Amanda Crawford-Adamo
Amanda Crawford-Adamo

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실습 문제하고 트랙하세요.

Google로 계속하기계속 진행하시면 다음 사항에 동의하는 것으로 간주됩니다: 이용약관 및 개인정보 처리방침 그리고 귀하의 데이터가 미국에 저장된다는 점에 동의하는 것으로 간주됩니다.

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.

Session Resources (Including GitHub Repo + Slides)

주제

Data EngineeringGitPythonDockerAirflow

관련

튜토리얼

Introduction to GitHub Codespaces

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