Data Engineer in Python Career Track
About this course
Data engineering is the fastest-growing specialization in the data field — building and maintaining the pipelines that make data accessible for analysis and ML. DataCamp's Data Engineer in Python track covers the Python data engineering stack: building ETL and ELT pipelines, orchestrating workflows with Apache Airflow, transforming data with dbt, querying cloud data warehouses with Snowflake, processing big data with PySpark, and managing data quality and testing.
The track is structured as a complete career path rather than isolated courses — each module builds on the previous, and the track culminates in a portfolio project. Data engineering salaries consistently exceed data science salaries in many markets, making this one of DataCamp's highest-value career tracks.
What you'll learn
This course includes
Compare alternatives for Data Engineer in Python Career Track
- Price
- PaidDataCamp subscription
- Duration
- 60 hrs
- Level
- Intermediate
- Certificate
- Career Track Certificate
- Price
- FreeCompletely free, openly licensed — no certificate
- Duration
- 34 hrs
- Level
- Intermediate
- Certificate
- Price
- FreeFree lecture materials; some versions paid
- Duration
- 50 hrs
- Level
- Advanced
- Certificate
- Price
- FreeFree lecture materials; some versions paid
- Duration
- 50 hrs
- Level
- Advanced
- Certificate
Instructor
Developed by DataCamp's data engineering curriculum team in collaboration with industry practitioners from leading data engineering companies.
Requirements
- Python and SQL fundamentals; DataCamp subscription required
Who this course is for
- Data analysts who want to transition into data engineering roles
- Software engineers who want to specialize in data infrastructure
- Anyone targeting data engineering, data platform, or analytics engineering roles