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Becoming a Better Data Engineer

1h 46m 10s
English
Paid

Data engineering is not just about moving information from one place to another. It is about creating reliable, scalable, and efficient systems that transform raw data into valuable insights. However, in practice, many engineers face chaotic tasks, switching from one problem to another—without a clear strategy and structure.

Course Overview

We created the course "How to Become the Best Data Engineer" to help you tackle real challenges in Data Engineering—from planning and designing systems to implementation and support. You will master proven approaches that allow you to prevent errors before they occur and build functional pipelines, rather than temporary solutions.

By the end of the course, you will apply a structured approach to any project, work more efficiently, and solve problems like a true professional—whether you are starting from scratch or looking to move to the next level.

What to Expect in the Course

Introduction to Data Engineering and Project Stages

You will understand the complete data path—from sources to storage and end users. Learn about the four key stages of a project: Planning, Design, Implementation, and Support, and why each is critical for success.

Avoiding Common Mistakes in Projects

Many engineers suffer from unclear requirements, unrealistic deadlines, and communication issues. You will learn to set measurable goals (KPIs), manage stakeholder expectations, and prevent scope creep.

Building and Optimizing Pipelines

A good pipeline is not just functional but also scalable, resilient, and maintainable. You will study data integration design, error processing, performance improvement, and reliability assurance on a long-term basis.

Support: Monitoring, Debugging, and Scaling

You will learn how to track failures, quickly find and fix errors, and scale infrastructure without extra costs.

About the Author: Andreas Kretz

Andreas Kretz thumbnail

I am a senior data engineer and trainer, a tech enthusiast, and a father. For more than ten years, I have been passionate about Data Engineering. Initially, I became a self-taught data engineer and then led a team of data engineers at a large company. When I realized the great demand for education in this field, I followed my passion and founded my own Data Engineering Academy. Since then, I have helped over 2,000 students achieve their goals.

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#1: Introduction
All Course Lessons (20)
#Lesson TitleDurationAccess
1
Introduction Demo
01:33
2
Data Engineers & What We Do
06:33
3
Phases Of Data Projects
05:35
4
General Areas To Improve
06:35
5
Understanding The Requirements Better
03:20
6
Not Forgetting To Analyze The Status Quo
07:19
7
Setting Good KPIs
06:06
8
Improving Estimation Of Implementation Efforts
04:58
9
Designing Better Platforms
06:10
10
Calculating Costs By Leveraging Pricing Models
06:20
11
Running Good Benchmarks To Make Right Platform Choices
06:50
12
Define Better Work Packages
04:00
13
Analyze & Avert Risks Like A Pro
06:53
14
Write Better Tests
06:05
15
Create Documentation That Actually Helps People
06:54
16
Great Monitoring & Alarming
06:08
17
How To Handle Bug Fixing Like A Pro
05:37
18
Create A Documentation For Ops
04:20
19
Continuous Improvement
03:35
20
Conclusion
01:19
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