What? How (and Where) to learn Data Engineering in 2022?

Last Updated 2 weeks ago

Data Engineers function behind the scenes and it could be in your best interests to learn Data Engineering.

In this piece, we probe to learn how you should pursue this goal and where you can learn the various intricacies of data engineering on your own.

So, let’s start

Data Engineering is primarily concerned with Information Engineering as to how the data will be organized, collected and used.

Data Engineers enable Data Scientists to probe for insights, apply Machine Learning, Algorithms, and other analytical approaches.

So, If want to learn Data Engineering, you must learn to work with all kinds of data assets starting from data storage systems, data pipelines, and data queries.

This however is not an easy job as most of the Big Data Projects fail due to a lack of reliable data infrastructures.

learn data engineering

In simple words, we can say that the Data Engineers build the foundation required to channel data into a format, useful according to its intended purposes.

For instance, If the pipe is rusty on the inside, the quality of the water will likewise savour rusty.

And, what would that yield but that which is not good for anything!

So, It’s very important to remember that Data Engineers hold the key responsibilities of Information Engineering to design and build the pipelines to transform and transport the data.

Since Data keeps abounding at a higher frequency, there are always new and more requirements to process raw data.

  • There are always requirements for Handling large-scale data processing.
  • Unique purposes to consolidate and enrich numerous datasets.
  • Better plans to monitor and maintain systems.

The image below should captivate your thoughts as to how significantly important Data Engineering is to the success of projects.

learn data engineering

There is an ever-increasing demand for Data Engineers and the average base pay for a Data Engineer in the U.S. is $115k!

Therefore, It would be in your best interests to pursue this goal.

It is one of the rising professions across the globe and the Payscale is remarkably better than so many tech professions.

And, now, let’s jump to learning how and where you can learn…


How (and Where) you should Learn Data Engineering in 2022?

Data Engineers are expected to possess sound skills in designing data models, building data warehouses and data lakes.

It’s important to learn every important concept related to Cloud Data Warehouses, Spark, Data Pipelines with applications like Apache Airflow and more.

You’ll also need to learn the basics of Machine Learning and Algorithms as you go along.

Moreover, you need to spend a lot of hours sharpening programming skills to automate data pipelines and develop the ability and interest to work with massive datasets.

If you are a beginner without any experience in computer science and all of this is seems unfulfilling to you —JUST DON’T FRET!

We hope you’ll stick to reading this piece as this may sound very intimidating but it’s not rocket science.

As a beginner, you need to keep in mind that you must learn to code all at your own pace.

There are three primary goals you should keep in mind when you begin

  • Build a foundation in programming
  • Learn about Databases for Data Engineering
  • Build data pipelines

So, 3 goals for beginners and if you are an intermediate-level learner, you’ll do fine on your own through the right career track.

Where should you Learn Data Engineering?

If you want to be a part of this groundbreaking science, devote a long-term commitment to learning.

In the next few sections, we’ll describe some high-quality learning tracks from Notable educators, taught by the most qualified Instructors.

And they’ll provide more clarity and more insight as to how you should start your journey, even as an absolute beginner!

So, let’s assess now!


Data Engineer with Python

This Data Engineering career track is developed by DataCamp and is suitable for beginners to learn from the basics of Python to build an effective data architecture, streamline data processing, and maintain large-scale data systems.

DataCamp Logo

DataCamp is excellent for beginners, offering a tremendous amount of learning resources to help you grow your skills as you work with Shell, SQL, and Scala.

Step by step, you’ll build the skills to develop data engineering pipelines, automate common file system tasks with Python, and construct a high-performance database.

What you will learn?

You will spend the first 2 hours understanding how data engineers lay the groundwork that makes data science and machine learning possible for companies.

Next, you will start with the basics of Python in context to Data Engineering and learn Pandas to acquire data from CSV files, spreadsheets, JSON, SQL databases, and APIs.

Then, You will learn to effectively write Python code and understand the best practices to write maintainable, reusable, complex functions with good documentation.

And the following modules will thoroughly explain to help you lean

  • Shell and Data Processing in Shell
  • Introduction to Bash Scripting
  • Unit Testing for Data Science in Python
  • Airflow in Python and PySpark
  • AWS Boto in Python
  • Relational Databases in SQL and Data Analysis in SQL (PostgreSQL)
  • Database Design
  • Introduction to Scala
  • Big Data Fundamentals with PySpark
  • Cleaning Data with PySpark
  • Introduction to MongoDB in Python
Data Engineer with Python
Source: DataCamp

Is this right for you?

The Data Engineering career track by DataCamp is suitable for anyone who has no experience in programming or knowledge of databases.

It is for absolute beginners who bring no experience and knowledge of programming or computer science.

DataCamp aims to help beginners gain a firm domain-specific foundation through a collection of courses in context to data engineering.

In order, you may be able to become a successful data engineer.

Upon completion, you’ll have acquired sound skills to work on real-world data engineering projects and be able to apply for jobs.

GO TO Data Engineer with Python


Data Engineering Career Path

Data Engineering Career Path by Dataquest is a beginner-friendly career track to learn every data engineering topic with guidance.

Dataquest Logo

This is career track is highly recommended to beginners as learning online can get frustrating, confusing, and unmotivating.

So, the instructors will guide you through the obstacles to master each technical skill needed to become a successful data engineer.

What you will learn?

First, You will master the basics of Python programming to learn each fundamental concept of Python programming in the context of data engineering.

And you will learn to use the Python data toolbox through a combination of lectures and exercises to improve your overall understanding of how Python works.

You will learn about Algorithm Complexity as you progress to reach a certain capacity of understanding to assess and implement efficient algorithms in Python.

You will also learn

  • Building Data Pipelines
  • PostgreSQL for Data Engineering
  • Data structure fundamentals
  • SQL Queries for Data Analysis
  • Optimizing for Large Data Sets using pandas
  • Recursion and Trees
  • NumPy for Data Processing
Data Engineering Career Path
Source: Dataquest

Is this right for you?

If you want to learn from scratch and can dedicate time to put solid efforts into completing this program, you’ll have the data skills recruiters look for.

You’ll master key tools in this program like pandas, NumPy, SQLite, MapReduce, and PostgreSQL.

This program is entirely hands-on and offers interactive teaching, so you’ll be able to stay focused with help to press onwards.

Upon completion, you’ll have the skills necessary to thrive as a data engineer, plus extras to stand out with the job-ready portfolio to showcase during the interview process.

GO TO —Data Engineering Career Path


Become a Data Engineer

This Data Engineering Nanodegree program is offered by Udacity in collaboration with INSIGHT to help learners build a solid foundation in Big Data Engineering.

b190d9cc udacity blue

Udacity is a credible leader in talent transformation, offering highly-quality programs in artificial intelligence, machine learning, cloud computing and the robotics sector, as well as data science.

In this program, you will learn everything important about designing data models, building data warehouses and data lakes, automating data pipelines, and working with massive datasets.

What you will learn?

The first course begins with learning relational and NoSQL data models to fit the diverse needs of data consumers.

You’ll learn the differences between different data models, and how to choose the appropriate data model for any given situation.

And, You’ll also get a thorough introduction to PostgreSQL and Apache Cassandra and conclude with 2 Course projects.

The next course will help you to create cloud-based data warehouses and you will sharpen your skills through guided lectures to deepen your understanding of data infrastructure with hands-on lab exercises.

You will also

  • Understand cloud computing
  • Set up Amazon S3, IAM, VPC, EC2, RDS PostgreSQL
  • Implement Data Warehouses on AWS
  • Learn Spark and Data Lakes
  • Learn Data Wrangling with Spark, Debugging and Optimization
  • Build and Automate Data Pipelines
  • Learn about Data Quality and Production Data Pipelines
  • Complete Final Capstone project
Learn Data Engineering
Source: Udacity

Is this right for you?

This Nanodegree program is suitable for Python programmers who have experience in SQL.

It’s is an excellent program for learners to gain a firm foundation in Data Engineering including cloud computing.

Each course in this program includes a project which will be evaluated by the Udacity reviewer network.

You will learn to solve important technical challenges and learn to work with massive datasets and gain an advanced familiarity with data engineering principles and techniques.

By the end, you will be highly prepared for job titles such as analytics engineer, big data engineer, data platform engineer, and others.

With an impressive portfolio of real-world projects and valuable hands-on experience.

GO TO Become a Data Engineer


Data Engineering, Big Data, and Machine Learning on GCP Specialization

This highest-rated Data Engineering Specialization is offered by Google Cloud to help learners become highly equipped in using TensorFlow, Bigquery, and Google Cloud Platform in the context of Data Engineering.

eeddba5a coursera

This program is delivered via Coursera, a leader in online education offering thousands of courses and specializations from World leading Educators and Organizations.

The high-quality courses in this specialization program will help you to build the data engineering skills you need to advance your career with skills in Machine Learning and Big Data as well.

What you will learn?

First, You will begin with an introduction to Big Data and Machine Learning fundamentals on Google Cloud.

Then you will learn about the big data capabilities of Google Cloud and get a thorough introduction to the data processing and machine learning capabilities.

Next, you will learn about Modernizing Data Lakes and Data Warehouses with Google Cloud.

You will understand the use-cases for each type of storage and learn about data lake and warehouse solutions on Google Cloud.

Furthermore, you will learn to create data pipelines for business operations, and dive deep into learning to build batch data pipelines on Google Cloud.

You will also

  • Build Resilient Streaming Analytics Systems on Google Cloud
  • Use BigQuery to conduct interactive data analysis
  • Learn Smart Analytics, Machine Learning, and AI on Google Cloud
  • Examine values Big Data and Machine Learning in Google Cloud
  • Evaluate data processing products on Google Cloud
  • Use Cloud SQL and Dataproc to migrate existing MySQL
  • Learn to use Hadoop/Pig/Spark/Hive workloads to Google Cloud
Learn Data Engineering
Source: Coursera

Is this right for you?

This specialization assumes comfortability with Google Cloud, Programming. Databases and understanding of Big Data.

It is suitable for learners who are already learning data engineering and desire to bootstrap their knowledge and experience of Data Engineering on Google Cloud.

The quality of the courses is very good and this Specialization incorporates hands-on labs using our Qwiklabs platform.

Upon completion, you will have increased your knowledge and understanding of Data Engineering, Big data, Cloud Computing and Machine Learning.

GO TO Data Engineering, Big Data, and Machine Learning on GCP Specialization


Closing Notes

Data engineering skills are helpful for adjacent roles as well, such as Data Scientists, Data Analysts, Cloud Practitioners, Machine Learning Engineers, or Software Engineers.

If you liked this article, please consider sharing it with your friends and colleagues and join our Data Science, ML & AI Newsletter.

We also have a few practical reads for you. One about Learning Geospatial Data Science and one about Kubernetes Certification Path.

Thanks for making it to the end : )

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