The Data Engineering Bootcamp: Zero to Mastery
Build scalable pipelines, data lakes, and streaming systems for data engineering roles
Created by Ivan Mushketyk
Gain practical experience building scalable data pipelines, data lakes, and streaming systems using Python, SQL, Spark, AWS, Airflow, and Kafka. Develop the core skills needed for modern data engineering roles and learn how to connect tools into production-ready workflows.
Packt | Jul 2026 | 1000 min
What You Will Learn
You will start with foundational skills in Python, SQL, and command-line work, then move step by step into large-scale processing, cloud-based data lakes, and workflow orchestration. Each section includes hands-on exercises and projects that mirror real data engineering tasks, helping you connect concepts to practical outcomes.
Key Features
- Create and manage batch and streaming data pipelines using Spark, Kafka, and Flink
- Build AWS data lakes and orchestrate workflows with Airflow for real-world scenarios
- Apply AI and machine learning tools like Spark ML and Hugging Face to data workflows
Target Audience
This course is ideal for aspiring data engineers, software developers, analysts, or anyone eager to work with scalable data systems. If you are comfortable with technical setup and want to gain hands-on experience in building pipelines, managing distributed processing, and integrating AI tools, you will benefit from this course.
