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Why you should become an data engineer

Data Science

Blog Date
August 14,

Key takeaways:

  • When it comes to data, data engineering is a crucial discipline.
  • Data drives the operations of both small and large organisations. Businesses use data to answer pertinent questions about everything from consumer interest to viability of their products.
  • Data is, without a doubt, a crucial component of growing your business and collecting insightful information. 
  • Working as a data engineer gives you an opportunity to directly impact society in a world where we’ll be producing 463 exabytes every day by 2025 and making data scientists’ lives easier.

Working in the field of data engineering can be challenging and satisfying. You’ll be a key player in a company’s success by enabling data scientists, analysts, and decision-makers to access the information they require to do their jobs. You’ll rely on your programming skills and analytical abilities to develop scalable solutions.

Data engineering skills are key to any organisation since data is always being processed. In India, the market for data engineering in 2022 stands at USD 18.2 billion. It is anticipated that this would increase during the following five years at a CAGR of 36.7%, reaching USD 86.9 billion by 2027. Of all non-IT businesses, banking and insurance employed the most data engineers.

According to Glassdoor (May 2022), the average pay for a data engineer in the US is USD 115,176. However, some data engineers make upto USD 168,000 annually.

Not all positions in data engineering are entry-level. In fact, many data engineers begin their careers as business intelligence analysts or software engineers. As your career develops, you might take on managerial duties or work as a solutions architect, data architect, or machine learning engineer.

What is data engineering?

A data engineer is an IT specialist whose primary duty is to provide data for analytical or operational use. They integrate, consolidate, and clean the data to prepare it for analytics systems. They aim to make data more accessible and enhance the big data environment within their company.

Data engineers use different amounts of data depending on the size of the organisation. As the organisation grows, the analytics architecture will get more complex, and the engineer will be responsible for more data. Teams of engineers and data scientists work together to promote data transparency and provide organisations with the resources they need to make more reliable business decisions.

The demand for data engineers

Big data engineers fall within the categories of statisticians and information and computer research scientists, according to the Bureau of Labor Statistics (BLS). The employment prognosis for each of these two categories is as follows:

  • Statistician: Starting from 2020 until 2030, jobs are expected to expand by 33%. The employment of computer and information research experts is expected to rise by 22% by 2030. 
  • Computer research scientists: The BLS estimates that demand for big data engineers jobs will rise drastically over the next four to five years, making this a promising career path to pursue, which is why most people want to be a data engineer.

Evolving field

Since the value of data is so widely acknowledged, it won’t be long until it appears on a company’s financial statements as an asset. Statista.com predicts that between 2020 and 2025, the amount of data/information produced/captured, transferred, and consumed globally will rise from 64.2 zettabytes to 181 zettabytes. However, sound data engineering is crucial for businesses to use that data efficiently.

A drawback of having a lot of data is that modelling it might be difficult. To prevent models from being fed inaccurate or irrelevant data, it is essential to comprehend and analyse data. Although discussions on maximising the value of data frequently centre on AI (artificial intelligence), machine learning, and algorithms, it’s crucial to consider how that data is strategically gathered, transformed, and distributed. 

Data engineers must ensure that the data supplied to business users is relevant, of high quality, and reliable for firms to profit from the data they have invested in gathering and maintaining.

Roles and responsibilities of a data engineer

The following is a list of the duties that are included in the data engineer job description:

Working on the data architecture, they plan, develop, and maintain data architectures systematically while keeping them in line with business needs.

  • Gathering data

The correct data must be gathered from appropriate sources before starting work on the database. Data engineers then store the processed datasets after creating a set of processes.

  • Industry research

Data engineers conduct industry research to solve problems that may come up while solving a business challenge.

  • Improve data engineering skills

Data engineers don’t just rely on abstract database theories. Regardless of the development environment that they are working in or their programming language, they must be capable. They must also keep up to date on machine learning and associated techniques, such as k-means, decision trees, and random forests.

Data engineers must be adept at using analytics programmes like Apache Spark, Tableau, and Knime. They must produce insightful business data for a variety of sectors using these methods. Data engineers, for instance, can make a difference in the healthcare sector by spotting trends in patient behaviour that can be used to enhance diagnosis and treatment.

ALSO READ: Data scientist job role and description

Data engineering skills and tools required

Data engineers need a variety of programming languages, data management tools, data warehouses, and other tools for data processing, data analytics, and AI/ML to develop such a robust data infrastructure. The following are some tools and data engineer skills they need to be proficient with.

Data warehousingPython
Knowledge of operating systemsPerl
Database systemsJava
Data analysisC and C++
Critical thinking skillsAmazon Web Services
Understanding of machine learningHadoop

Industries that require data engineers

Data usage has dramatically increased during the last few years. More people, groups, companies, etc., are using data in their regular operations. People used to place a greater emphasis on insightful analysis and insights, but they have since realised that maintaining data demands just as much attention. Data engineer skills are in high demand in almost all industries. Listed below are some of them.

  • Healthcare and pharmaceutical

It takes careful consideration to launch a career in the healthcare industry. Therefore, if you choose to enter it, be sure that you are prepared to deal with facts that may be related to people who are having a difficult time with their lives. 

Therefore, working in this field is a humanitarian endeavour, and you must be cautious while developing your data science strategy to provide the most insightful solutions to data problems.

  • Telecommunications sector

Mind Commerce estimated that the big data and data science industries will help the telecom sector develop at a compound annual growth rate of 50%, with annual revenue reaching from USD 59 billion in 2019 to over USD 105 billion in 2023. Because of the readily available analytics software, data storage prices have significantly decreased, and computer processing power has increased. Consequently, a data engineer’s job description has become simpler.

Because of the data obtained from customer behaviours like voice, video preferences, SMS, social media activity, and demographics, telecom companies can offer personalised services and products.

  • Internet industry

The data explosion brought on by advanced technology, big data, and cloud computing is now strengthening the internet sector. Data scientists have an incomprehensible amount of data at their disposal, which they use to create personalised recommendations, conduct sentiment analysis, analyse videos, etc. 

With billions of people using the internet, sharing images and videos on social media, and conducting Google searches every second of the day, it is no surprise that the internet sector, e-commerce, and social networks are thriving to an inconceivable extent.

Opportunities & hiring companies

Data engineering is the new gold of the 21st century. Here are a few companies that provide the eBay opportunity to start a career.

  • Amazon
  • CBRE
  • Allied Universal
  • Aya Healthcare
  •  Humana
  • PwC
  • Marriott International
  • Northwell Health
  • UnitedHealth Group
  • JPMorgan Chase
  • Aramark Corporation
  • Verizon
  • Randstad US

Career growth options

Like any job in software engineering, a data engineering roadmap can take you through different avenues. You might advance to the status of a key contributor. Additionally, you might manage a group of engineers. The data engineer roadmap is quite big and worth exploring, to begin with.

Pay scale

According to Glassdoor, the average Data Engineer salary in India is Rs. 8,56,643 LPA. Of course, a number of variables affect a data engineer’s compensation, such as the company’s size and reputation, location, educational background, position held, and experience. 

Data engineers are typically paid well by reputable businesses and major participants in the Big Data sector, including, but not limited to, Amazon, Airbnb, Spotify, Netflix, IBM, Accenture, Deloitte, and Capgemini. Additionally, your market value will increase the more Big Data-related employment experience you have.

How to become a data engineer?

You can begin or advance your data engineering career with the right abilities and knowledge. By acquiring a degree, you may lay the foundation for the information you’ll need in this rapidly changing sector. To expand your career and open doors to opportunities with possibly greater salaries, consider getting a master’s degree.

You can take a number of different actions in addition to getting a degree to position yourself for success.

  • Improve your knowledge of data engineering
  • Earn a credential by enrolling a data science programme
  • Create a portfolio of work, including data engineering
  • Pursue an internship
  • Apply in a entry-level job


Closing remarks 

It is a great time to think about becoming a data engineer, given the continual increase in demand for data analytics and Big Data opportunities in India and beyond. It is predicted that there will be more career opportunities in the data science field in future. 

Visit Online Manipal’s website if you’re interested in learning more about data engineering. They provide an M.Sc. in Data Science programme online. Expert faculty from Manipal Academy of Higher Education (MAHE) has designed the curriculum, which prepares future-ready professionals. From the comfort of your home, you can  become an expert in data science and thrive in your career.


Information related to companies and external organizations is based on secondary research or the opinion of individual authors and must not be interpreted as the official information shared by the concerned organization.

Additionally, information like fee, eligibility, scholarships, finance options etc. on offerings and programs listed on Online Manipal may change as per the discretion of respective universities so please refer to the respective program page for latest information. Any information provided in blogs is not binding and cannot be taken as final.

  • TAGS
  • data science
  • Online MSC Data Science

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