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- Data
Python for Data Engineers
The Python for Data Engineers skill path focuses on leveraging Python’s powerful libraries and frameworks to handle data ingestion, transformation, and analysis at scale. It covers key tools like Pandas, SQLAlchemy, PySpark, and Airflow for data pipelines, ETL processes, and automation. This skill set enables data engineers to build efficient, scalable data workflows for analytics and machine learning applications.
Content in this path
Python for Data Engineers
Watch the following courses to get started on your Python data engineering journey.
Try this learning path for free
What You'll Learn
- How to connect to databases to extract data with Python
- How to build and deploy ETL pipelines with Python
- How to automate data pipelines and orchestration with Python
- How to log, monitor, and debug data pipelines with Python
- How to build messaging systems with Python
- How to perform scalable data processing with Python
- How to perform streaming data processing with Python
- Learners interested in this path should have basic Python knowledge, including an understanding of Python syntax, functions, and data structures. Learners should also have experience using pandas for data processing and knowledge of handling large datasets. Finally, learners will benefit from an understanding of SQL.
- Python
- Data Engineering
- SQL
- ETL
- Stream Processing





