Data Engineering is vital across many industries, as businesses use data to make informed decisions.
Organizations that use data to spur business strategies often find that they are more confident, proactive, and profitable.
Data Engineering is technical and a leading profession with strong job security. Each year, there is more demand for data engineers and cloud data engineers than there are people with the right data skills to fill those roles.
Data Engineer is one of the fastest-growing job in 2022, growing by 50% YoY offering superb earning potential.
Before you dive into learning, realize that data engineers lay at the intersection of software engineering and data science.
You'll need to gain proficiency in statistical programming languages for software engineering, such as Python, R and Scala.
You are required to learn critical data engineering skills for most job roles, including big data frameworks, building data pipelines, database architectures, data infrastructure, cloud data engineering, and more.
If you are a beginner with no experience in computer science, here are a few helpful tips for getting started.
- Nail the data fundamentals
- Routinely learn to build skills
- Learn from your mistakes
- Practice with data projects
- Join a data community
- Build your skills bit by bit
In this article, we have provided a review of some high-quality learning tracks that can help you gain a comprehensive knowledge of data engineering both in physical and cloud environments.
Data Engineering Certification Programs and Specialty Courses
Data Engineering is relatively new and disruptive. It’s important to ensure that you’re taking a data engineering course tailored to your background and experience level.
These courses will also provide an in-depth overview of the modern data ecosystem with insights into how the roles like data analysts, scientists, and engineers play in data management.
Below, we have listed down the best courses to learn Data Engineering.
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.
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.
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.
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 the context of Data Engineering and learn Pandas to gain data from CSV files, spreadsheets, JSON, SQL databases, and APIs.
Then, you will learn to write the Python code and understand the best practices to write maintainable, reusable, complex functions with good documentation.
Objectives
- 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
Is it 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 data engineering.
Upon completion, you’ll have gained sound skills to work on real-world data engineering projects and be able to apply for jobs.
GO TO — Data Engineer with Python
Data Engineer Career Path
Data Engineering Career Path by Dataquest is a beginner-friendly (mentor-led) career track to learn every data engineering topic with guidance.
The instructors will guide you through the obstacles to master each technical skill needed to become a successful data engineer.
We highly recommended this career track to beginners, as learning online can get frustrating, confusing, and unmotivating.
What you will learn?
First, you will master the basics of Python programming to learn each fundamental concept of Python programming in 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.
Objectives
- 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
Is it 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 Engineer 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.
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 for 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 data model for any 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 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.
Objectives
- 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
Is it right for you?
This Nanodegree program is suitable for Python programmers who have experience in SQL.
It 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
Google Cloud offers this highest-rated Data Engineering Specialization to help learners become highly equipped with using TensorFlow, BigQuery, and Google Cloud Platform in Data Engineering.
This program is delivered via Coursera, a leader in online education offering thousands of courses and specializations from World leading Universites, Educators and Organizations.
The high-quality courses in this specialization program will help you 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.
You will learn to create data pipelines for business operations, and dive deep into learning to build batch data pipelines on Google Cloud.
Objectives
- 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
Is it 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 Note
Data engineering skills are helpful for adjacent roles as well, such as Cloud Data Engineering, Data Scientists, Software Engineers or Machine Learning Engineers.
These resources will help you build a strong foundation of programming, big data frameworks, cloud computing and more.
We also have a few practical reads for you. One about Data Engineering Skills and one about Data Scientist Skills.
Thanks for making it to the end.