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The Data Engineering Bootcamp: Zero to Mastery

Learn Data Engineering end-to-end. Build real-time pipelines with Apache Kafka & Flink, data lakes on AWS, machine learning workflows with Spark, and integrate LLMs into production-ready systems. Designed to launch your career as a future-ready Data Engineer.

28 Days

Average time students take to complete this course.

instructor
Taught by: Ivan Mushketyk
Last updated: July 2025

Rated 4.9 out of 5 on Trustpilot

What you'll learn

  • Learn the skills and real-world tools used by Data Engineers and become top 10% in your field
  • Build stream-processing pipelines with Apache Kafka and Apache Flink
  • Create scalable, cloud-based data lakes on AWS using S3, EMR, and Athena
  • Develop distributed processing jobs with Apache Spark and orchestrate workflows with Apache Airflow
  • Future-proof your skills by learning to integrate AI & machine learning including using Spark ML and LLMs
  • Build real-world, production-ready projects and pipelines using popular open source software

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.

When's the best time to get started? Today!

There's never a bad time to learn in-demand skills. But the sooner, the better. So start learning Data Engineering today by joining the ZTM Academy. You'll have a clear roadmap to developing the skills to build your own projects, get hired, and advance your career.

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What you'll build

The best way you learn is by doing. Not just watching endless tutorials. That's why a key part of this course is the exercises you'll complete and the massive real-world project that you'll get to build. Plus they'll look great on your portfolio.

Clean, Join & Analyze Airbnb Data with Apache Spark

Clean, Join & Analyze Airbnb Data with Apache Spark

Explore the Inside Airbnb dataset by writing Spark jobs that clean, join, and analyze real-world Airbnb listings and reviews. Learn how to submit and fine-tune Spark applications like a pro.

Your First Data Lake on AWS

Your First Data Lake on AWS

Build your first modern data lake from scratch! You'll combine AWS tools like S3, EMR, and Athena to set up scalable, queryable storage that's ready for real-world analytics.

Workflow Orchestration with Apache Airflow and Spark

Workflow Orchestration with Apache Airflow and Spark

Orchestrate data workflows using Apache Airflow and Spark. Build pipelines that read, validate, and process booking and review data from Postgres, all while handling retries and failures.

Make Predictions using Machine Learning with Spark

Make Predictions using Machine Learning with Spark

Train scalable Machine Learning models that predict house prices and booking cancellations. Use Spark ML to perform feature engineering, evaluate models, and run experiments.

Integrate AI with Data Engineering for Sentiment Analysis

Integrate AI with Data Engineering for Sentiment Analysis

Tap into the power of LLMs to classify customer reviews and generate structured JSON. Learn how to integrate them into Spark workflows for real-time NLP processing.

Real-Time Data Processing & Anomaly Detection with Flink

Real-Time Data Processing & Anomaly Detection with Flink

Use Flink to enrich, join, and analyze streaming order and payment data in real-time. Build applications that detect anomalies and track metrics as events happen.

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Course curriculum

To make sure this course is a good fit for you, you can start learning Data Engineering for free right now by clicking any of the PREVIEW links below.

Section 00 - Introduction

5 lectures

The Data Engineering Bootcamp: Zero to Mastery1:34

PREVIEW

Exercise: Meet Your Classmates and Instructor

PREVIEW

Course Resources

PREVIEW

ZTM Plugin + Understanding Your Video Player

PREVIEW

Set Your Learning Streak Goal

PREVIEW

Section 01 - Introduction to Data Engineering

7 lectures

Section 02 - Big Data Processing with Apache Spark: Process & Analyze Real-World Airbnb Data

28 lectures

Section 03 - Creating a Data Lake with AWS

16 lectures

Section 04 - Implementing Data Pipelines with Apache Airflow

25 lectures

Section 05 - Machine Learning with Spark ML: Create a Data Pipeline, Train a Model + more

25 lectures

Section 06 - Using AI with Data Engineering: LLMs, HuggingFace + more

11 lectures

Section 07 - Real-Time Data Processing ("Stream Processing") with Apache Kafka

24 lectures

Section 08 - Stream Processing with Apache Flink

19 lectures

Where To Go From Here?

6 lectures

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Meet your instructor

Your Data Engineering instructor (Ivan) isn't just an expert with years of real-world professional experience. He has been in your shoes. He makes learning fun. He makes complex topics feel simple. He will motivate you. He will push you. And he will go above and beyond to help you succeed.

Ivan Mushketyk

Hi, I'm Ivan Mushketyk!

Ivan is a data & software engineer with 12+ years of experience designing and scaling distributed systems. His career spans early-stage startups and industry leaders, including AWS and Stripe, where he built production-grade cloud and data applications.

SEE MY BIO & COURSES

Ivan Mushketyk

Data Engineer

Frequently asked questions

Are there any prerequisites for this course?

  • Basic Python knowledge is required. If you don't have that we recommend taking the first few sections of our Python Bootcamp course, which is included in your ZTM Academy membership.
  • Basic SQL knowledge is required. If you don't have that we recommend taking the first few sections of our SQL Bootcamp course, which is included in your ZTM Academy membership.
  • Familiarity with using the Shell / Terminal is recommended.

Who is this course for?

  • Beginners looking to launch their career in the in-demand field of Data Engineering
  • Developers looking to upskill or future-proof their career and break into Data Engineering roles
  • Software Engineers who want to build data platforms and pipelines, not just APIs
  • Data Scientists, AI Engineers, and Machine Learning Engineers who want to understand the infrastructure behind their models
  • Data Analysts ready to level up and move into engineering
  • Engineers interested in working with large-scale batch and streaming systems
  • Anyone curious about how to use LLMs in real-world data pipelines
  • Learners who prefer hands-on exercises and project-driven learning over theory-heavy tutorials

Do you provide a certificate of completion?

We definitely do and they are quite nice. You will also be able to add Zero To Mastery Academy to the education section of your LinkedIn profile as well.

Can I use the course projects in my portfolio & resume?

Yes, you’d be crazy not to! We help you build really impressive projects and all projects are downloadable and ready to use the minute you join. They are also customizable so you can make them your own.

Many of our students tell us the projects they built while following along with our courses were what got them interviews & jobs! Because they were able to built the projects themselves, they could confidently explain and walk through their work during the interview.

You know what that means? Job offer!

Are there subtitles?

Yes! We have high quality subtitles in 11 different languages: English, Spanish, French, German, Dutch, Romanian, Arabic, Hindi, Portuguese, Indonesian, and Japanese.

You can even adjust the text size, color, background and more so that the subtitles are perfect just for you!

Still have more questions about the Academy?

Still have more questions specific to the Academy membership? No problem, we answer some more here.

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