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RADE™ Apache Airflow on AWS (MWAA)

Orchestration, Monitoring, and Control of Real-World Data Pipelines

Course Summary

Apache Airflow is not a core requirement to become a data engineer.
But when combined with strong fundamentals, it becomes a clear career differentiator.

This course is part of the RADE™ Career Differentiators for Data Engineers track —
designed to help capable engineers stand out in interviews and system-design discussions.


 Who This Course Is For

This course is ideal for you if:

  • You already understand core data engineering concepts
    (SQL, ETL pipelines, Spark/Glue, data warehousing basics)

  • You want to move beyond “script-based pipelines”

  • You want to confidently explain:

    • How pipelines are scheduled

    • How failures are handled

    • How dependencies are managed

  • You see Airflow as a way to strengthen your resume and interview profile

  • You want real orchestration experience without running Airflow infra yourself

  • You are preparing for mid-to-senior data engineering interviews

This course is especially valuable if:

  • Your current role does not expose you to Airflow

  • You want system-level talking points for interviews

  • You want to look stronger than “Spark + SQL only” candidates

 Who This Course Is NOT For

This course is NOT recommended if:

  • You are new to data engineering

  • You are looking for a tool-only crash course

  • You expect Airflow to teach you data processing
    (Airflow is orchestration — not Spark/ETL execution)

  • You want Airflow to replace core skills
    (it won’t — and shouldn’t)

 If your fundamentals are weak, this course will not help —
it is meant to amplify, not compensate.

 What You Will Be Able to Do After This Course

By the end of this course, you will be able to:

Think Like an Orchestration Engineer

  • Explain why Airflow exists and where it fits in a data platform

  • Clearly differentiate Airflow from Step Functions and EventBridge

  • Use Airflow only for orchestration, not heavy processing

Build and Operate Real DAGs

  • Deploy and manage AWS MWAA

  • Write clean, production-grade DAGs

  • Configure retries, schedules, catchup, and dependencies correctly

  • Pause, resume, and manually trigger pipelines safely

Handle Real-World Scenarios

  • Implement failure notifications and callbacks

  • Wait for external data using sensors

  • Use dataset-based dependencies for data-aware pipelines

  • Pass metadata safely using XCom

  • Make pipelines configurable using Variables

Explain Airflow Confidently in Interviews

  • Walk through Airflow architecture and components

  • Answer scenario-based interview questions clearly

  • Explain trade-offs and design decisions

  • Demonstrate practical understanding — not buzzwords

 Hands-On & Assessment Coverage

This course includes:

  • Guided hands-on exercises on AWS MWAA

  • Practical DAG development scenarios

  • Interview question frameworks

  • MCQ-based knowledge validation

  • Assignments that simulate real-world orchestration patterns



 Live Practice Component (Important)

In addition to recorded content:

  • A live session will be conducted

  • Students will actively:

    • Explore the Airflow UI

    • Work with DAGs

    • Observe orchestration behavior

    • Apply concepts interactively

The live component focuses on doing, not theory repetition.

Core skills qualify you.

Career differentiators make you stand out.

This course does not make you a data engineer.
It makes a good data engineer look stronger.

Course Curriculum

Sachin Chandrashekhar

John Smith

Developer

Highly Recommended Course. Easy to Understand, Informative, Very Well Organized. The Course is Full of Practical and Valuable for Anyone who wants to Enhance their Skills. Really Enjoyed it. Thank you!!

Course Pricing

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