Data Engineering Roadmap

A Data Engineer is a data professional who collects, transforms, and process data according to the need of the business. Data Engineering is one of the highest-paying jobs in Data Science. So, if you are looking for a roadmap to learn Data Engineering, this article is for you. In this article, I will take you through a complete roadmap for learning Data Engineering with learning resources you can follow for learning Data Engineering step by step.

Data Engineering Roadmap

Here’s a complete roadmap you can follow to learn Data Engineering step by step:

1. Start with Python
2. Learn Databases
3. Learn Data ETL Pipelines
4. Learn Machine Learning
5. Learn Big Data Tools
6. Learn Cloud Computing

Now let’s explore each step of the roadmap one by one.

Step 1: Learn Python

The first step in this Data Engineering roadmap is to learn Python. Python is one of the most valuable programming languages for data professionals. Below are some resources you can follow to learn Python:

1. Python Full Course by Tech with Tim
2. Introduction to Python programming by Udacity
3. Think Python

Step 2: Learn Databases

As a Data Engineer, one of your key responsibilities will be to manage the data according to the need of the business. So you need to know about the databases to manage the data of your organization. Below are some of the best resources you can follow to learn Databases:

1. SQL for Data Scientists
2. SQL Tutorial by FreeCodeCamp
3. Seven NoSQL Databases in a Week

Step 3: Learn Data ETL Pipelines

Creating ETL pipelines is one of the most valuable skills for Data Engineers. In an ETL pipeline, you need to write reusable code to extract, transform, and load data according to the need of the business. Below are some of the best resources to learn Data ETL pipelines:

1. Data Pipelines Pocket Reference
2. ETL and Data Pipelines with Shell, Airflow, and Kafka
3. ETL in Python Course by Datacamp

Step 4: Learn Machine Learning

Now the next step is to learn Machine Learning. Machine Learning means using data and algorithms to build intelligent systems. While learning machine learning, you need to focus on the theory of machine learning algorithms and their implementation using Python. Below are some of the best resources you can follow to learn Machine Learning:

1. Hands-on Machine Learning with Scikit-learn, Keras, & Tensorflow
2. Machine Learning Crash Course by Google Developers
3. Machine Learning Algorithms: Handbook

Step 5: Learn Big Data Tools

The next step in the Data Engineering roadmap is to learn big data tools. Below are all the big data tools you should learn for data engineering:

1. Apache Hadoop
2. Apache Spark
3. Apache Kafka
4. Apache Airflow
5. MongoDB

Step 6: Learn Cloud Computing

Cloud computing is an essential skill for every data engineer. Below are some of the best resources you can follow to learn cloud computing:

1. Introduction to Cloud Computing by Udacity
2. Introduction to Cloud Computing by IBM
3. Learning AWS – Second Edition

Summary

So below is the complete roadmap for learning Data Engineering:

1. Start with Python
2. Learn Databases
3. Learn Data ETL Pipelines
4. Learn Machine Learning
5. Learn Big Data Tools
6. Learn Cloud Computing

I hope you liked this article on a roadmap to Data Engineering with learning resources. Feel free to ask valuable questions in the comments section below.