How to Become a Data Engineer in 2022

     Today we will discuss The Path to Becoming a Data Engineer in 2023. Unlike a data scientist who analyzes and interpret complex data and a data analyst who analyzes numeric data, Data Engineer is someone who involves in preparing the data. 
 The Path to Becoming a Data Engineer in 2023

  • Data Engineer develops, constructs, tests, and maintains complete architecture.
A data analyst requires advanced knowledge of programming for analyzing large datasets and data scientists require a high knowledge of programming language to analyze and make machine learning models and deploy them but a Data engineer needs an intermediate knowledge of programming to build thorough algorithms and require higher statistics skills. 
   The complete list of skills which a data engineer should have are:

·         Data Warehousing and ETL
·         Advance programming knowledge
·         Hadoop based analytics
·         In-depth knowledge of SQL/database
·         Data architecture and pipelining
·         Machine learning concept knowledge
·         Scripting, reporting and data visualization


How and from where to start?

     Many of you may be getting worried after seeing the skills listed above. Don’t worry because below is the list of courses which I recommend you should take in-order to start your journey towards data engineering:
        This course is a Nanodegree program provided by Udacity and the amount of knowledge you will get from this Nanodegree is sufficient to start your career as a data engineer in the industry but you need to practice your skills before that.
   This link will open a webpage where you will find all the courses which are on Coursera for data engineering. This page will tell you the prerequisite you need before you go into data engineering and it will also tell you the courses you require to become a data engineer.
      Google cloud is a trending tool for Data Science and Data engineering. Many companies who hire data engineers want their employees to have expertise in these types of tools. In this course apart from the knowledge you will be working on different projects and at the end of this course, you will be taught how you can prepare for the google cloud professional data engineer exam.
       Linkedin is a professional website on which you can find your dream job and know it launches a new LinkedIn learning program where you can learn and earn certificates and you will get your first month for free.
   In this course you will learn all the concepts that you need to know about data engineering and this course consists of 10 items after which you will get your certificate.


  •   Create and maintain optimal data pipeline architecture 
  •    Assemble large, complex data sets that meet functional / non-functional business requirements.
  •   Identify, design, and implement internal process improvements: automating manual processes, optimizing data delivery, re-designing infrastructure for greater scalability, etc.
  •   Build the infrastructure required for optimal extraction, transformation, and loading of data from a wide variety of data sources using SQL and AWS ‘big data’ technologies.
  •   Build analytics tools that utilize the data pipeline to provide actionable insights into customer acquisition, operational efficiency, and other key business performance metrics.
  • Work with stakeholders including the Executive, Product, Data, and Design teams to assist with data-related technical issues and support their data infrastructure needs.
  •  Keep our data separated and secure across national boundaries through multiple data centers and AWS regions.
  •  Create data tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader. 
  •  Work with data and analytics experts to strive for greater functionality in our data systems.


Top Companies hiring data engineers:

Top Companies hiring data engineers

     You must be thinking about 
is there a big company that hires data engineers at a good package? So, the answer is Yes. There are a lot of companies who hires data engineers in India as well as abroad.

Top companies hiring data engineers are:
  •   Google
  •   Amazon
  •   Microsoft
  •     IBM
  •   Intel
  •    Netflix
  •    Flipkart
  •   Goldman Sachs
  •     Walmart Labs
    If you are thinking that before applying to big MNC’s like that are listed above you should work for small companies to get experience then I must say you are on right track. In the next section, you will see where you can apply to get your dream job or to start with a small company.

Where to apply?

     You don’t need to worry that how you will get the job. Today there are many social media platforms where you can apply for a job without giving any consent fee. The top social media platforms where you can find your dream job are:
           Linkedin are an American business and employment-oriented online service where you can connect with HRs, your fellow students, Companies and you can easily apply to jobs here.
       Before getting into a full-time job role many students wants to work as an intern in the company so they can understand the working environment of the company don’t worry Internshala is there for you. Here you can apply for internship easily and many students are getting internships from the Internshala platform
3.           For more resources I suggest you search the web about the role and your dream the company you will find that if your dream company is currently hiring for this role or not and if yes then you can directly apply to it.

Average salary of Data Engineers:

    After doing so much study and working with different tools like Google cloud and NoSQL databases you might be thinking about how much you will earn.

data engineer vs data scientist salary

    I must say that you should not worry about your salary because in India the average salary of a data engineer is Rs. 8,68,951 per annum and if you see the statistics about the salary in this field then you will see a growing graph because it grows with time as the requirement of data engineers in the industry is getting higher.
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