The 3 Biggest Realisations I’ve Had As Data Engineer

The 3 Biggest Realisations I’ve Had As Data Engineer
Photo by Judeus Samson on Unsplash

Self-Belief, Self-Improvement, and Self-Education

One of my favourite proverbs is a Haitian one about overcoming obstacles:

Beyond mountains, more mountains.

If you work in data engineering, I think you can agree that you can easily apply that wisdom to a data engineer’s journey: when you think you’ve grasped one thing or solved one problem, something else turns up to flip it all on its head.

Mountains, mountains, mountains — everywhere!

Data issues, endless courses, errors, tools upon tools, boot camps — like I said, mountains everywhere!

Simply put, data engineering is not for the faint-hearted, nor is it boring.

This is true for every project, from the simplest to the most complex. As your experience grows, the more you learn, and the better you get at wrangling data — bending it to your will.

The work you do and the ideas you have will grow more ambitious.

After a few years of trying to figure out this data engineering thing, I’ve realized that data engineering is a balancing act. These are the three realizations I’ve come up with.

1. Self-Belief (Trust Yourself)

What‘s missing in the data community? — self-belief.

It sucks, but it’s happening. I talk with loads of data engineers, and they all say the same things. No one feels good enough.

Everyone feels like they are playing catch-up, and behind the scenes, data engineers quietly battle with self-doubt and a persistent feeling of being inadequate.

On the road to data engineering success, you will face many challenges. It’s all too easy to doubt your abilities, but what I’ve learned in my time is that data engineers are all different. We all have unique skills and abilities to bring to the table.

If you’re good at SQL, lean into that; if it’s Python, use it to your advantage, then pick up the rest as you go.

You don’t have to learn everything under the sun. You need to know enough to do your job — the rest will fall into place.

Some Things That Helped Me:

  • Comparison breeds insecurity and self-doubt — Don’t compare yourself to others in your team or Joe Blogg on LinkedIn with fifty thousand followers. Focus on yourself and your skills. Then slowly level up and play the long game.
  • Find out what you are good at and hone your skills further. Time is on your side.
  • Learn and adapt — Throw yourself into tasks that scare you. Push through self-doubts. You learn more out of your comfort zone. Don’t hide away.

Believing in yourself and your skills can be a game-changer.

Build that self-belief.

2. Self-Improvement (Getting Better)

With every project, there are going to be easy days and hard days. Every day, there are going to be problems that seem to solve themselves and problems that make you wonder if you even know what you are doing.

On days like these, see these problems as opportunities to learn and grow. If you’re looking for something to keep you going as a Data engineer remember:

  • Data Engineering rewards continuous improvement. The more you do it, the better you get.
  • There is always something you can do to improve yourself and your skillset, so keep on grafting.

Progressing as a Data Engineer means always pushing yourself through those tough times.

You should always be looking for ways to improve and grow.

3. Self-Education = Progress

The smartest thing you can do as a Data Engineer right now is self-educate.

It sounds so simple, but I see so many people waiting around for something to happen, waiting for some kind of divine light or Data Engineering fairy to guide them on their path.

It’s not coming. There is no data engineering fairy.

  • Don’t wait for your company to put you on a course.
  • Don’t wait for someone to tell you what you should learn.
  • Don’t wait for the right time.

Put your head down and work hard. Never wait for things to happen. Make them happen for yourself through hard graft and not giving up.

Continuous self-education is the key to staying on top of everything. It’s the difference between an average data engineer and a good one.

Final Thoughts

My journey as a data engineer was not a straight line, and the traffic lights of life have not always been green for me. My story is more of a path with many forks in the road, a few mishaps, and plenty of lessons along the way.

The biggest lesson I’ve learned over the years is that to become good at anything, let alone data engineering, it’s a balancing act of self-belief, self-improvement, and, most importantly, self-education.

Never stop learning. Build from the ground up and make things happen.


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