Are you ready to master the art of building robust and efficient data pipelines in the cloud?

Are you interested in advancing your career in data engineering or improving your cloud expertise?

If so, our Building and Managing Data Pipelines in the Cloud course is perfect for you.

Learn the art of cloud-based data engineering from course instructor Shashank Kalanithi, a seasoned professional with extensive experience in the data and tech industry. Shashank has held various roles including data analyst, data scientist, data engineer, and is currently a software engineer at Meta. His passion for teaching, coupled with his hands-on expertise, ensures that you’ll receive not just knowledge but actionable insights that you can apply directly to your work.

Why is this course perfect for aspiring data engineers?

Gain an understanding of cloud-based data pipelines and how they differ from traditional on-prem systems.
Explore the three major cloud providers—AWS, Azure, and GCP—and the tools they offer for data engineering.
Build a strong foundation in data orchestration, transformation, storage, and monitoring using cloud-native tools.
Learn how to ensure cost efficiency, optimize resources, and maintain security for your cloud pipelines.

Why is this the perfect course for current data professionals?

Enhance your expertise in managing complex cloud pipelines and reducing costs through best practices.
Deepen your understanding of tools like AWS Glue, Azure Data Factory, Google Cloud Dataflow, and more.
Learn how to handle challenges like pipeline failures, outages, and scaling resources effectively.
Gain insights from Shashank’s real-world experience to tackle common pitfalls in cloud-based data engineering

Building and Managing Data Pipelines in the Cloud starts with an introduction to cloud computing fundamentals and the benefits of cloud data engineering. You will learn about key orchestration tools like Apache Airflow and cloud-native solutions such as AWS MWAA, Azure Data Factory, and Google Cloud Composer. The course covers everything from designing ETL/ELT pipelines to leveraging data storage solutions like AWS S3, Azure Blob Storage, and Google BigQuery.

You’ll also dive into advanced topics like:

Pipeline reliability and failure management
Cloud security practices like secrets management and role-based access controls
Cost management strategies to ensure pipelines are efficient and scalable
Tools for monitoring and logging such as AWS CloudWatch, Azure Monitor, and Datadog

Finally, you’ll explore real-world scenarios and case studies to understand how to create scalable, secure, and cost-effective pipelines that meet business needs.

This course is designed to prepare you for the challenges of cloud data engineering and to give you a comprehensive toolkit for success.

Get ready to revolutionize the way you think about data pipelines. Start your journey today!

Building Data Pipelines with Apache Airflow