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Roadmap for Becoming a Data Engineer in 2023

In the world of Big Data, professionals with the expertise to work with data to help support smart decision-making processes are in huge demand. Data is rendered the fuel of the 21st century.

Take a peek at some impressive statistics about the Big Data and Engineering industries.

  • The global market size of Big Data and Engineering services is projected to grow from USD 130.7 billion in the year 2020 to USD 234.6 billion by the year 2025, which is a CAGR of around 10.2%, according to a report by Global Industry Analytics Inc.
  • The Dice 2020 report state that the year-over-year growth for data engineering job roles is expected to grow by a whopping 50%
  • A report by the US Bureau of Labor Statistics states that around 11.5 million new job roles are expected for Data Analytics, and Science related positions
  • The average annual salary of a Data Engineer in India is around INR 8.2 lacs and may go as high as INR 21 lacs or even more
  • Some of the well-established names looking for Data Engineers include Microsoft, Facebook, IBM, Ericsson, Accenture, Deloitte, Google, Amazon, Apple, Walmart, and more
  • Data Engineers and other data experts are in demand in almost every sector, including BFSI (Banking, Financial Services, and Investment), Healthcare and Pharmaceuticals, IT, manufacturing, and more

The stats clearly state that there is a massive demand for professionals with skills in data analytics as a result of the ongoing wave of digital transformation, automation, and artificial intelligence.

This is why there is a surge in the number of professionals taking Data Engineer Courses to pave their way for making a career in this ever-growing domain.

This blog will help you define your career path to becoming a Data Engineer.

What is Data Engineering?

Data Engineering is a facet of Data Science that primarily focuses on the practical approach to creating a robust and reliable infrastructure that can maintain consistent data flow in a data-driven environment by maintaining the processes of collecting and pipelining the data.

Who is a Data Engineer?

A Data Engineer is a tech pro who can build and maintain the data pipeline and data processing system of an organization by cleansing and wrangling it to make sure that the data obtained is reliable and usable.

As a Data Engineer, you will be required to facilitate the processes of collecting and cleaning the raw data from different sources and converting it into a user-readable format. You will be mainly responsible for generating high-quality data. It may include steps such as developing, installing, testing and maintaining the finest quality data to accomplish business objectives.

Some common responsibilities of a Data Engineer include:

  • To perform exploratory data analysis
  • To extract data from a vast pool of raw information
  • To evaluate and cleanse data sets
  • To prepare and write the logic for the ETL pipeline (Extract, Transform, and Load)
  • To construct data pipelines for distribution across various servers
  • To mine and perform querying of data
  • To integrate the data together
  • To create data repositories
  • To optimize the processes of data delivery
  • To normalize and perform modeling of data
  • To redesign data infrastructure for scalability
  • To utilize the framework for serving data
  • To help data scientists in the optimization of products

How to Become a Data Engineer?

Some of the most crucial steps to becoming a Data Engineer are mentioned below.

  1. Acquire a Bachelor’s Degree in Appropriate Field

A majority of data engineers acquire a bachelor’s degree in mathematics, science, or any other relevant data-related domain to form a strong foundation. You will acquire a solid understanding of basic concepts of programming and an entry-level job with a bachelor’s degree in software engineering. To get hands-on practice with tools and techniques, you can work on real-world projects and build a diverse portfolio for career guidance.

  1. Attain expertise in the required skills

You need to brush up on your command of programming languages, big data skills, and databases.  You can begin by learning the foundational concepts of SQL so that you can query the data. It is also important to learn how to use database architectures, model data, build data pipelines, work with raw data, and perform data mining.

Additionally, to advance your skillset, you can learn different ways of processing big data in streams or batches. Also, you can learn different tools, including Hadoop, Kafka, etc., to organize workflows in big data environments.

  1. Master Programming Languages

Programming languages form the core of the tech industry. The two major programming languages that are required for a Data Engineer include Python and Scala. You should fine-tune your skills in these programming languages. You should acquire a firm grip on some most important programming languages, such as Python, C++, Java, and Scala. To attain proficiency in these languages, you can take online training and certification courses.

  1. Master the concepts of Cloud Computing

You should know well how to work seamlessly with cloud computing and different services offered by cloud platforms, such as computation, cluster management, cloud storage, networking, and data processing management.

  1. Get Certified

Professional certifications are the best way to advance your career in Data Engineering. There are many Specialization certifications, certification courses, and Master’s qualifications that promise to equip you with the most crucial technical skills, including scripting, automation, Kafka, Java, Tableau, distributed systems, and many more. This may also include ETL/ELT technologies like Hadoop and Airflow, streaming concepts like Apache Beam, and more.


Data Engineering is an ever-growing domain and the best time to make a career in this field is NOW!!

There are many online training courses that can help you advance your career in Data Engineering. Simplilearn is a one-stop solution that can help you accomplish this goal. Real-world projects based on current data, hackathons, certifications, Ask Me Anything sessions, training delivered via industry experts, and career guidance make this course worth your investment of time and money.

Enroll Yourself Now!!