Data Engineering Roadmap (2026)

Coursera · Intermediate ·🔄 Data Engineering ·7mo ago

Key Takeaways

The video discusses a Data Engineering Roadmap for 2026, covering tools such as SQL, Python, Spark, Airbyte, Airflow, dbt, and DuckDB, as well as cloud pipelines and warehouses.

Full Transcript

We should say [music] it's just a little too late, a little too wrong. And I can't wait.

Original Description

DE Roadmap 2026 SQL → Python → Spark Airbyte → Airflow → dbt Warehouses + DuckDB Cloud → Pipelines Save this | Follow @Coursera #coursera #dataengineer
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The video provides a roadmap for data engineers in 2026, covering key tools and technologies such as SQL, Python, Spark, and cloud pipelines. It highlights the importance of data engineering in managing and processing large datasets. By following this roadmap, data engineers can develop the skills needed to design and implement efficient data pipelines and warehouses.

Key Takeaways
  1. Learn SQL and Python fundamentals
  2. Explore Spark and its applications
  3. Familiarize yourself with Airbyte, Airflow, and dbt
  4. Understand cloud pipelines and data warehouses
  5. Implement DuckDB for data storage and analysis
💡 The key to successful data engineering is to have a solid understanding of the tools and technologies involved, as well as the ability to design and implement efficient data pipelines and warehouses.

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