Hiring can be tricky. Strike that. Hiring the right person can be tricky. It’s the crucial stage at which business development can be helped along hugely or scuppered by recruiting an unsuitable employee to a key role.
Every recruitment process has certain dos and don’ts, which can vary depending on the position you’re seeking to fill. Generally speaking, the more complex the position, the more exacting will be the demands that apply to the selection process. You need to be sure that the individual you pick will be able to do the job better than any other candidate in the field.
Great data engineers don’t grow on trees. Their skills aren’t commonplace, just as everyone doesn’t share their personality traits. But don’t despair. There are certain techniques you can apply when hiring data engineers that will give you the best chance of getting your hands on the right person for the job.
What are the Best Data Engineer Characteristics?
When an individual is performing data engineering services, there are specific skills they should have that will help them do this to a high standard. Coding’s a no-brainer. Well, it’s not – that’s the problem. It requires a great deal of brain power to do well. So, you’re looking for evidence that they’ve done coding before in a high-performance environment.
Communication’s another skill that some technicians can perhaps demonstrate too little of. A data engineer’s findings often have to be disseminated to groups that are less technically proficient, so an ability to talk about data in a way that’s accessible to the general population will be helpful.
An awareness of the requirements of data security is of paramount importance, especially in terms of developments such as the Internet of Things. So some experience in this area will be useful. The importance of upskilling and staying current with the latest technologies and trends in the industry cannot be overstated for data engineers.
Skilled data engineers need to display a healthy amount of critical thinking and problem solving, so they need to have a personality that’s well matched to these abilities. They also need to show a propensity for innovative work, as originality will be key to their and the company’s success. Less excitingly, they need to be able to sit down and error-check.
Any experience they can exhibit in any of these fields will be very helpful in your quest to find qualified candidates. On top of this, there are certain practices you can deploy to give yourself an even better chance.
One useful technique in the recruitment process is phone search, which can help you identify potential candidates beyond those who have applied directly. By expanding your search beyond just the pool of applicants, you increase the chances of finding the best candidate for the job.
1. Make Yourself Attractive
Your business is looking for a new special somebody. When we do this kind of thing as individuals, we pay special attention to our appearance to attract the right kind of attention. It’s just the same with businesses.
Start by ramping up your profile so that your business name becomes synonymous with interesting work. One of the most effective ways you can do this is to post original content concerning, for instance, your unique Agile transformation strategy or any other fields you want your data engineers to specialize in.
The sooner you start featuring on data engineers’ lists of the best companies to work for, the better. Then, when job opportunities come up, it’s more likely that those most suited to the work and culture involved will apply.
For example, if you’re working at a finance software development company, showcasing your expertise in data engineering and your success in delivering financial solutions can make your business more attractive to potential candidates in the field.
2. Act Fast
Data engineers are in hot demand right now, so if your hiring process takes too long to complete, you may lose your ideal candidate. Accordingly, if you see an application you like, get in touch right away and interview ASAP.
Continue at this pace right through the selection process: keep it short and focused—no point in having extra steps if they just get in the way. Once a candidate proves themselves a good choice, send out the paperwork and get the hiring done without delay.
3. Outsource Where You Can
Most businesses don’t have the means or desire to tie up vast amounts of resources in maintaining a recruitment division. So, it makes sense to use the services of others where you can. This is particularly the case with specialized recruitment for rarefied roles like data engineering.
When using a partner for the task, you will have a chance to use goal tools to demonstrate your business objectives so that you can be sure of ending up with a highly suitable field of candidates who will contribute well to your business success.
4. Interview Well
Remember to think about how the company comes across to the applicant. They may have a few irons in the fire, so they might be only too happy to jettison yours if you come across as unprofessional or otherwise unsuitable. This applies across all stages, from interview invitation to notification of results.
Also, really listen to what the candidate says. It’s very easy for interviews to become box-ticking exercises. They can be so much more. Feel free to follow up on any leads that the conversation throws up so that you can get a fully-rounded picture of the applicant.
Additionally, consider incorporating a practical component into the interview process, such as a coding challenge or a data engineering task, to allow candidates to showcase their skills and problem-solving abilities. This will give you the opportunity to create your own assessment and gain deeper insights into their technical capabilities and fit for the role.
5. What Are You Offering?
Most high-performing candidates will be looking for two things: a great salary and great tech. Make sure that both are competitive. Salary requirements are hugely important. The base salary for junior data engineers in the US is around $60,000-$70,000. The average annual salary across the sector is significantly higher.
In terms of tech, you need to be sure that the stack you’re working with is up-to-speed and sufficiently powerful to pique interest. For instance, if your business primarily involves data engineering with Python, are you using the most helpful libraries, such as Psycopg2 and Great Expectations?
6. Always Be Clear
Make an effort to be very clear about the parameters of the engineering job you are offering to reduce the chance of subsequent role confusion among engineering teams or between engineers and non-tech staff. Ambition is all very good, but there has to be a specific division of labor, or discord can result.
Find the Right Fit for Your Company
By keeping in mind a broad range of techniques and applying them to your selection process, you’ll be in with a better chance of hiring the right experienced data engineer to add to your company team.
This leads to a very important point to finish on. Always remember that all businesses are different. A good data engineer in one organization might be so-so at best in another. So, be sure to factor your particular business’ characteristics front and center when hiring data engineers. Be loud and proud of them.
This way, you’ll be more likely to find the best-fit candidates. And the unsuitable candidates will hopefully de-select themselves.