A Super Helpful Month-by-Month Plan to Become a Data Engineer in 2024

Sakshi Raheja Last Updated : 23 Feb, 2024
4 min read

Overview 

  • This article will help you to achieve your career goal to become a Data Engineer in 2022
  • We will take you through a learning path that will help you structurize your learning efforts to become a Data Engineer

Introduction

Data Science is still considered a contemporary and highly advanced field. Everyone wants to be associated with something which is very trending. Right? So, if you’re planning to become a Data Engineer, then I would like to congratulate you!

Data Engineering is an emerging field that is highly intertwined with the Data Science field with the heterogeneity of job opportunities. The market leaders like Google, Twitter, and Tesla are all generating data at an unprecedented pace. Just imagine, the amount of data that needs to be tackled on an everyday basis!

By adopting Big Data Technologies, the data engineers make sure that this huge volume of data that is coming in at a high velocity, can be transformed and transported to its destination where it needs to be stored properly and efficiently and put to use as and when required.

Data Engineering

With this much demand in the market, it is imperative to have a practical learning path to structurize and optimize your learning to become a valuable data engineer in 2022 and have a fruitful career.

This learning path has been adapted from the free course – A Comprehensive Learning Path to becoming a Data Engineer in 2022. You can check out the course to get all the resources structured according to the month-on-month plan.

 

Monthly Plan 

Below is the monthly plan which is going to be your go-to guide for the year 2022. If you follow our planner and are passionate, then by the end of the year, you will be able to begin a career as a Data Engineer.

January – Learn Programming

The first month of the New Year should definitely set the tone for your professional journey. You need to be self-disciplined and structured by devoting a fixed number of hours each day. So, let’s start with the basics and take one step at a time towards your Data Engineering Career. It is important for you to learn to program.

  • Learn programming in Python
  • Solve basic python problems on HackeRank

February – Understand Relational Databases

Let’s now move forward and try to understand the relational databases. It is important for you to get comfortable with writing SQL commands using MySQL.

The reason why we want you to start with MySQL is that it is the most commonly used RDBMS used by most of the giants in the industry.

March – Fundamentals of Linux and Cloud Computing

This month, we will learn the fundamentals of Linux and Cloud Computing. Focus areas for this month will be:

  • Basic Linux Commands
  • Basics of Cloud Computing

Month 4 –  NoSQL Databases

In the month of April, we will move to the NoSQL Databases where we will learn about:

  • Different types of NoSQL databases
  • Basic querying in MongoDB

Month 5 – Hadoop Ecosystem

Let us understand a very important open-source framework that is intended to make the interaction with Big Data easier. This framework is known as Hadoop Ecosystem.

  • Overview of the Hadoop Ecosystem
  • Understand MapReduce processing
  • Understand the working of YARN

Month 6 – Data Warehousing

Let’s dive deeper into the course and now learn data management system which is known as Data Warehousing. Here, we will focus on:

  • Understand the concept of Data Warehousing
  • Work with Hive Query Language in Apache Hive

Month 7 – Data Visualization

Now, we will learn about Data Visualization which is an interdisciplinary field that helps us to formulate large sets of data in form of charts and graphics. Organizations believe that it is one of the most attractive techniques to gauge customers’ attention. Well, we all tend to have long-lasting memories of the visuals as compared to the text. Isn’t it?

  • Learn About Tableau
  • Try connecting Tableau dashboards with any database and programming language

August & September – Apache Spark

We will cover one of the most relevant tools of the current times in these two months, Apache Spark. For those who don’t know, Apache Spark is a distributing processing system that is used for big data workloads. It helps to utilize the memory-catching and optimized query execution for fast analytic queries.

We will cover the below aspects of Apache Spark:

  • Understand Spark components and processing
  • Work with Spark RDDs and DataFrames

 October – Handling Streaming Data

With humongous data, it is important for Data Engineers to learn the art of handling streaming data. Here, you will learn:

  • Understand what is Data Streaming
  • Work with DStreams
  • Get acquainted with stateless and stateful transformations

November – Kafka

No matter how hard you work, the most important thing is to have the results in ‘real-time’. With the world moving so fast, we can’t afford to leave any opportunity to be the best. In this month, you will learn about Kafka which is used to build real-time streaming data pipelines and applications that adapt to the data streams.

  • Learn Kafka architecture
  • Create topics
  • Code your first producer and consumer

December – Airflow

Let’s quickly get equipped with Airflow before we say bye to 2022. Airflow is the python based open source orchestration tool. Here, you will learn about:

  • Learn about the airflow DAGs
  • Pass data between 2 different tasks
  • Build a project that includes most of the tools that you have studied

And, that’s a wrap with Airflow!

So, are you excited to begin your Data Engineering Career?

Here is an infographic of the monthly plan as in the Comprehensive Learning Path to becoming a Data Engineer in 2022

Data Engineering Career

Conclusion

Once you’re able to successfully complete this planner. You can definitely land into a career as a Data Engineer with a leadership role that will expect you to wear different hats on the go. So, once you complete this planner, I would recommend you to work on your communication skills, structured thinking ability, and overall personality development which will help you to land the right job! After all, recruiters are always on the lookout for perfection.

Once you finally get your dream job, don’t get complacent. Stay up-to-date with the relevant trends of the industry like this is one of the fastest-growing industries.

Comment below if you need a mentor who will be able to guide you in your professional journey! I’ll be happy to connect you with some of the experts from our team. You could also visit our website for courses.

I am a passionate writer and avid reader who finds joy in weaving stories through the lens of data analytics and visualization. With a knack for blending creativity with numbers, I transform complex datasets into compelling narratives. Whether it's writing insightful blogs or crafting visual stories from data, I navigate both worlds with ease and enthusiasm. 

A lover of both chai and coffee, I believe the right brew sparks creativity and sharpens focus—fueling my journey in the ever-evolving field of analytics. For me, every dataset holds a story, and I am always on a quest to uncover it.

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