This Data Engineer at EY who dropped out of CA course shares why non IT professionals should aim for careers in Data.

 why non IT person should aim to become Data Engineer

Data engineering is one of the fastest-growing careers in technology, according to the Dice Tech Job Report.

Meet Vishant Kush, who dropped out of the Chartered Accountancy course midway and later was employed by EY as a Data Engineer.

Though coding is an essential aspect of data engineering, you don't have to be a coder to work in the industry, says Vishant.

You began with Chartered Accountancy, then moved on to a more demanding role as a data engineer at EY. Tell us how it happened.

After 12th, I opted to pursue CA, just as many commerce students did in India. However, after the second year of my articles, I realised that CA was not for me.

Dropping out of the CA course with no future plans was a difficult decision for me. But I had no choice but to accept it, regardless of what others thought.

Soon I learned about Global Business Operations, a two-year postgraduate degree (GBO), and went ahead with it. 

I was later recruited in Research by EY.

In my post-graduate programme, I also learnt analytics. So during the orientation process when I learned that they had an opportunity in data analytics, I switched over without any second thoughts.

What is your role at EY? Is it strange to have a financial background on a team full of traditional data engineers?

My responsibilities as a data engineer at EY involve, among other things, developing data models, automating manual processes, developing analytical tools, and experimenting with big data. 

Part of my job entails communicating with clients, which necessitates a combination of consulting and analytics skills.

Yes, I am the odd one out of the team with a financial background, but that is my strength. 

When we have to construct an analytical solution or something that includes financial principles, or involves calculating the current ratio, my strong financial abilities come in handy.

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What technical skills were required for the Data Engineering role?

I only knew Excel, Power BI, SQL, and a bit of Python before moving into data engineering.  I learned the rest of the important skills at work, such as Alteryx (Data Science and Analytics Automation Platform). 

If there is going to be a project that requires UiPath (Business Automation Platform), I’d have to start learning.  

That is the beauty of this career path, the learning doesn’t end. 

I use websites like Udemy for relevant courses. But that’s not enough, as I have to also put the learnings into practice through projects. 

There are websites for that as well so that we can get hands-on experience. 

I connect with people on LinkedIn and ask them to give me some tasks that I was learning about. 

What skills are essential for data engineers?

Excel is something which everyone should know; not just the basics but advanced ones like Power Query, VBA, formulas, Macros etc.

Everything we perform using other different tools can be done in Excel. You can even automate a process using Excel. 

Critical thinking plays a big role. You need to have analytical thinking and problem-solving skills. 

Sometimes you’d receive a requirement from a client, in business terms. You have to convert those into technical terms and deliver solutions to clients that optimize their processes and meet their business requirements.

If the client says that he needs a business process to be done in 4 hours instead of 1 week, you have to do that using different technology.

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Is coding necessary to become a Data engineer?   

 Coding is an integral part of data engineering; we have to use coding for Data Loading, Data cleaning, etc. You must learn about various ETL (extract, transform, load) tools. Despite that, it’s not mandatory for you to be a coder, to get into data engineering.

We do several tasks without coding and as surprising as it may sound, I have never written a single line of code over the last five months of joining EY.

I use different tools like Alteryx, for data cleaning, which can also be performed in SQL (programming language), but it’s up to the company, and the individual.

What is the future growth of data engineering?

Data Engineering and Data Science are two of the highest-paying jobs out there. 

Data is the future, and if any company wants to win the competition they need to be future-ready.  They can only achieve that through data. The mode of presentation has changed from PowerPoint to Power BI. 

That is why almost all companies are now hiring data engineers, and it's not just Big 4, or Fortune 500 exclusive job roles. 

Don’t believe the misconception that only engineers or computer science graduates are fit for this role. Anyone who is interested in analytics, and drawing insights from data can opt for this. 

As a Data Engineer, you can shift to Data Analytics and Data Science roles as well and even move into consulting and other roles. 

Moving up the hierarchy, this role will get you to managerial positions, and over time you can become an Assistant Manager, Domain Leader and even Director. 

Did you know

As per Glassdoor the national average salary for a Data Engineer is $114,518 in the United States, and in India, it is ₹8,00,000 per year.

Since roughly 2016, demand for Data Engineers has exceeded supply. 

Data is the new oil. According to the World Economic Forum, by 2025, over 463 exabytes (an exabyte is 10006 bytes) of data would be generated globally every day. This clearly indicates that there will be an increase in the need for data engineers.

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