The Data Engineer Masterclass is a hands-on training program designed to help learners master the core components of data engineering. Across 20+ sessions, you will learn how to build batch and real-time data pipelines, automate workflows, and manage cloud-based infrastructure using Python, Spark, Airflow, and Kafka. This course prepares you for modern data engineering roles in enterprise and startup environments.
About Course
This course teaches the complete lifecycle of a Data Engineer. You'll start by learning the basics of data processing and storage, move on to advanced topics like distributed computing, and finish with real-world projects. Topics include SQL, Python for data processing, building ETL/ELT workflows, and working with data warehouses like BigQuery and Redshift.
No, the course teaches Python and SQL from the ground up.
Yes, it covers batch (ETL) and real-time streaming using tools like Apache Spark and Kafka.
The course includes AWS, Google Cloud, and Azure for data engineering workflows.
Yes, you'll use tools like Apache Airflow and cloud schedulers for automation.
Absolutely—projects use real-world datasets with complete pipeline development from ingestion to reporting.
What Will You Learn?
- Python for Data Engineering – Learn to write scalable and modular code for extracting, transforming, and loading data across various sources.
- Advanced SQL for Big Data – Master joins, window functions, CTEs, and optimization techniques for handling large datasets.
- Building ETL/ELT Pipelines – Design and implement data pipelines for batch and near real-time ingestion using industry best practices.
- Apache Spark – Process large-scale data efficiently with RDDs and DataFrames using PySpark for distributed computing.
- Apache Airflow – Create and manage complex workflows with DAGs to automate and monitor your data pipelines.
- Streaming with Kafka – Ingest real-time data using Apache Kafka and integrate it with consumer systems.
- Cloud Platforms – Store and query data using AWS S3, Redshift, and GCP BigQuery.
Audience
This course is ideal for aspiring data engineers, backend developers looking to transition into data roles, and analysts wanting to build strong infrastructure knowledge.
Course Content:
Understanding the role of a data scientist
Key concepts in data science
Overview of the data science process
Python programming basics
Data manipulation with pandas
Data visualization with matplotlib and seaborn
