Top 4 Mistakes NOT to Make
to Become the Best Data Engineer in the World
So, you’ve realized that you want to become a big data engineer. Smart move. But not just any big data engineer–the best in the world! Even better.
It’s a challenging and rewarding profession in very high demand. But just because there’s a massive shortage of data engineers, doesn’t mean your career path is guaranteed. Here are four mistakes the best big data engineers of tomorrow won’t make today.
1. Join a small company that thinks about “doing something with data.”
It’s great that companies want to start “doing something with data.” But if they don’t have a clue about what that is yet, they most likely won’t have the right knowledge-sharing, data-driven, working culture or people to make things happen. These companies can’t kickstart your big data engineering career if they can’t even get their own thing off the ground. Sure, they might promise you a lot of freedom, but in the end, without a vision or strategy underlying this “something-with-data” plan, you’ll be working on useless proofs of concept that end up in a drawer. What’s more, if you’re a self-starter, and the only data engineer in the company, who’s going to mentor you to achieve your potential? As a junior data engineer, you want to be surrounded by senior data engineers who will show the ropes. Small companies like these will just slow you down.
2. Apply at a corporate that says it’s completely data-driven, but actually isn’t.
So, if a small, inexperienced company is out, does that mean a big corporation is better? Not necessarily. It could be a smart move if there are other data engineers there who could teach you everything they know, but only if you’re 100 percent sure it absolutely is, indeed a data-driven organization. And even if it is, worst case scenario, your sole role as a data engineer there could be to combine different Excel files and clean dirty data sets. And that is not how you become the best data engineer in the world! So, don’t sign a contract before you lift the veil. Is there a professional data engineering and data science team in the company? What do they do? Can you learn from them? Do they have the full support of the C-suite? Is there a data strategy? If not, your big data dreams could die on the vine there
2. Choose a trainee program below your level.
Ok, a trainee program is definitely going in the right direction, but not if it’s below your level. As a data engineer just starting out, you might be tempted to apply for a traditional trainee or high-potential program with an employer who promises to focus fully on your development as a data professional. But if you already have a few years of experience under your belt and have proven your potential, these types of programs might not provide what you need. Do your homework before you sign up. Make sure you know what the program includes, precisely, and if the organization that offers it is mature enough to nurture YOUR potential. Otherwise, instead of learning from your colleague, you might end up teaching them.
Wait–what? But traveling makes you a richer (albeit poorer), more worldly, wiser and better person. True. But if you want to become the best big data engineer in the world, take a different kind of journey and focus on your career. The momentum is now.
So, what should you do instead?
Have you finished a master’s degree in the fields of computer science or software engineering? Are you eager to work with the latest data technology? Do you feel passionate about achieving your highest potential and becoming the best data engineer in the world? If yes, then you should kickstart your data engineering career by applying to Xcellerated’s one-year advanced development program. Our approach stems from deep-rooted values established by our founders – Xebia Group and GoDataDriven–organizations working on the bleeding-edge of IT consultancy for over 15 years. We foster your potential and transform you from a top-class starter into an experienced consultant. After a short boot camp, you will immediately start working on meaningful assignments at a data-driven organization, like Heineken or ING. You will learn while on the job, working as a big data engineer surrounded by experienced professionals. After one year, you’ll have the opportunity to transfer to the data-driven organization where you worked. And, of course, you also get paid during the program. So, don’t make the mistake of slowing down your big data dream. If you want to become the best big data engineer in the world, accelerate your career!