Data Engineering is the Big New Job in Tech

Data Engineering has rapidly become one of the fastest-growing and most in-demand tech careers today. The field has seen a remarkable remarkable year-over-year growth (25% to 50% depending on the source), as businesses across industries ramp up their data infrastructure to support AI, analytics, and real-time applications.

In fact, over 20,000 new Data Engineering jobs were created last year alone, pushing total job openings in North America to approximately 150,000 - a clear sign of an industry that's gaining serious momentum.

The earning potential for Data Engineers is just as impressive. U.S. professionals in this field enjoy average base salaries that start at $80,000–$110,000 for entry-level roles and can scale up to $190,000–$200,000+ for senior-level positions.

What makes Data Engineering even more attractive is the strategic role it plays in modern tech. Data Engineers are the backbone behind AI systems, machine learning models, and analytics platforms, making them absolutely vital to development of modern products and continuous innovation.

That means as the AI industry continues to explode, Data Engineering will explode alongside it.

This has led to a significant talent shortage that’s driving up salaries and increasing remote work flexibility. Compared to Data Science, Data Engineering remains a less saturated yet faster-growing field, creating the potential for long-term career growth and job security.

Why this Data Engineering Bootcamp course?

Because this Data Engineering Bootcamp is focused on being comprehensive but efficient, while teaching you everything you need to become a Data Engineer step-by-step.

You'll start with Apache Spark, where you'll learn how to crunch massive, real-world Airbnb datasets using code. Then, you'll move on to building a modern data lake on AWS - no fluff, just real tools like S3, Elastic Map Reduce, Glue, and Athena. You’ll orchestrate your data pipelines with Apache Airflow and dive into streaming with Kafka and Flink to build real-time systems. And so much more!

Plus you’ll be at the forefront of the data engineering world by getting hands-on experience building stream processing applications using Apache Kafka and Apache Flink, and even incorporating Machine Learning, AI, and LLMs directly into your data workflows.

By the end, you'll know how to build end-to-end, production-grade data systems...the same skills hiring managers are actively looking for.

So you never have to waste your time on confusing, out-of-date, incomplete tutorials anymore.

And you'll be learning data engineering in a fun and supportive environment with your instructor and other ZTM students, all while working at your own pace!

That's because by enrolling today, you’ll also get to join our exclusive live online community classroom to learn alongside thousands of students, alumni, mentors, TAs and Instructors.

Most importantly, you will be learning from an industry expert that has actual real-world experience working as a Data & Software Engineer for some of the largest companies including Amazon and Stripe.

Here is what the course will cover to take you from Zero to Data Engineering Mastery:

The curriculum is presented in basic building blocks so that you can build your knowledge step-by-step.

We start from the very beginning by teaching you why data engineering is so important and in-demand. Then we dive in to building projects using the real-world tools that actual Data Engineers use in their day-to-day jobs.

By the end of this course, we know you're going to fall in love with Data Engineering!

Here's a high-level overview of what's covered in this Data Engineering Bootcamp:

Introduction to Data Engineering
Get a clear roadmap of what modern data engineering looks like and ensure your setup is ready to go. This section also introduces key prerequisites like Docker and virtual environments.

Big Data Processing with Apache Spark: Process & Analyze Real-World Airbnb Data
Learn to harness the power of Apache Spark to process large datasets efficiently. You’ll work with the DataFrame API, UDFs, aggregations, and tune Spark jobs for real-world performance.

Creating a Data Lake with AWS
Create a scalable data lake using S3, EMR, and Athena. Understand columnar data formats and build a modern storage solution for batch analytics.

Implementing Data Pipelines with Apache Airflow
Learn how to coordinate data tasks using Airflow. You’ll build reliable workflows, handle retries and failures, and run Spark jobs and data ingestion tasks smoothly.

Machine Learning with Spark ML: Create a Data Pipeline, Train a Model + more
Build ML pipelines using Spark’s scalable ML library. From classification to regression and model tuning, you’ll integrate intelligent insights into your data pipeline.

Using AI with Data Engineering: LLMs, HuggingFace + more
Explore how LLMs can fit into the data engineering stack. Use Hugging Face and Outlines to classify, transform, and generate structured output within Spark workflows.

Real-Time Data Processing ("Stream Processing") with Apache Kafka Dive into Kafka and build robust streaming applications. Learn about producers, consumers, data ingestions, Kafka transactions, and build data pipelines that process incoming data in real time.

Stream Processing with Apache Flink
Use Flink to perform complex stream processing. Work with keyed streams, event time, joins, and build responsive, intelligent streaming apps using Kafka data.

What's the bottom line?

This course is not about making you just watch along without understanding the principles so that when you are done with the course you don’t know what to do other than watch another tutorial... No!

This course will push you and challenge you to go from a beginner and turn you into an Data Engineering master 💪.

How do we know?

Because thousands of Zero To Mastery graduates have gotten hired and are now working at companies like Google, Tesla, Amazon, Apple, IBM, JP Morgan, Facebook, Shopify + other top tech companies.

They come from all different backgrounds, ages, and experiences. Many even started as complete beginners.

So there's no reason it can't be you too.

And you have nothing to lose. Because you can start learning right now and if this course isn't everything you expected, we'll refund you 100% within 30 days. No hassles and no questions asked.