data engineer examining a data server

Data Engineer: An analytics role in high demand

Written on September 28, 2020 by Jonathon Webley

Here at Agile Recruit, we refer to data engineers as being like the construction workers of data.  After all, they are the ones that lay the foundation on which business can build their data collection, gathering and storage strategy, and they also make sure that the data collected is usable as well.  They are also responsible for making sure that the data is cleaned up and analysed at every stage of the data pipeline – so that it is ready for the other data professionals on their team to be able to use it for their Machine Learning models and for any reports they need to run.

Why is data analytics so important this year?

We don’t have to tell you that this year has been a funny one for businesses all over the world, with the COVID-19 pandemic having a great impact. However, as the world is slowly getting back to normal, and businesses are finding their feet again – whether that be by staying working remotely or reopening as they were before – the demand for data engineers seems to be higher than ever.  Data engineers are needed in order to lay the groundwork needed for businesses to succeed in today’s environment – whether that be through data modelling, machine learning or computer applications. The world has moved even more online since March this year, and so data is the driving force behind everything.

If you really want your business to succeed in 2020, and moving forward, then having a data team with a robust data plan which is aligned with your business strategy is essential. Getting ahead of the curve now is a surefire way to beat your competition by making better business decisions, which will lead to increased customer engagement and improved customer retention.

Data Scientists will be the first to tell you that they couldn’t do their job without Data Engineers. Data Engineers are the people who create reliable and efficient data systems because they understand the amount of data required, the speed at which it needs to be collected, and the wide variety of data needed as well. So it should come as no surprise that Data Engineers are in high demand at the moment, although there does seem to be a shortage of them – as with other data professionals as well.

This shortage has led to many professionals from other backgrounds retraining to become Data Engineers in order to fill the shortage. Whether they have planned to or are forced to as it is a business necessity, they can then manage the data pipeline and automate projects and help guide them through to the end.

What career opportunities are there within Data Engineering?

As the demand for data continues to grow, it has created more and more opportunities for those who perhaps haven’t gone down the traditional study route for data engineering.  While some people may have a software engineering or other IT-related study behind them – many businesses are choosing to upskill other existing employees who they think have the talent to make a success of the data engineering role.

However, there is still a shortage of talent needed to fill the existing gaps – and it is critical that this gap is filled in order for businesses to continue to succeed. It is interesting to note that in LinkedIn’s “Emerging Jobs Report” for the United States in 2020, that both data and artificial intelligence continued to make a “strong showing”  with “data science booming and starting to replace legacy roles.” They also go on to say that among the top 15 emerging jobs in the US are: “Artificial Intelligence Specialist, Robotics Engineer, Data Scientist, Full Stack Engineer, Site Reliability Engineer, Data Engineer, Cybersecurity Specialist, Back End Developer, Cloud Engineer, and JavaScript Developer.”

What should you do if you want to become a data engineer?

Having a foundation understanding of maths, computer science or other business-related degree is always a good start, and from there you should look at:

  • Popular programming languages such as Amazon Web Services (AWS), Hadoop, Spark and SQL
  • Investing in further education and professional development to keep developing your skills and making sure they are up to date
  • Getting an entry-level role so that you can build up your knowledge on the job

The more hands-on experience you can get as a data engineer the better, especially if it is coupled with academic achievements.

If you are looking for your next data opportunity, or are wanting to fill a gap within your existing team, take a look at our current jobs or get in touch with one of our expert data recruitment consultants to find out how we can help.