A Data Engineer builds systems for collecting, processing, and storing data, enabling organizations to transform raw information into reliable insights for business decision-making. As the volume of data generated by companies continues to grow, Data Engineering has become one of the most in-demand fields in the IT industry.

Throughout this course, you will learn how to work with databases, program in Python, develop modern data pipelines, and process large-scale datasets using tools and technologies widely adopted by data engineering teams around the world.

What Will You Learn?

The course is designed to guide you step by step through the world of Data Engineering through hands-on work with real datasets and practical projects. During the program, you will gain experience with:

• Git and GitHub for version control and team collaboration
• SQL for working with relational databases
• Python for data processing and transformation
• Pandas and working with various data formats
• ETL and ELT pipeline development
• Databricks and the Delta Lake platform
• Apache Spark and PySpark for large-scale data processing
• Medallion architecture (Bronze, Silver, and Gold layers)
• dbt for data transformation, testing, and documentation
• Apache Airflow for data pipeline orchestration and automation