Hi, and welcome to another 365 Data Science special!
In this video, we’ll explore one of the top careers in data science.
That’s right – we’ll talk about becoming a data engineer.
You’ll discover who the data engineer is, what they do, how much they make, and what
education and skills you need to become one.
But before we get started…
We’d like to mention something else we’ve put together! – a very comprehensive data
science training.
The 365 Data Science program contains the full set of data science courses you need
to develop the entire skillset for the job.
It’s completely beginner-friendly.
For example, if you don’t have any maths or statistics knowledge, we’ll teach you
that first.
And if you’d like to build a more specialized skillset, you can do that with courses on
Time Series Analysis, Credit Risk Modeling and more.
If you’d like to explore this further or enroll using a 20% discount, there’s a link
in the description you can check out.
Alright.
Let’s talk about the data engineer and everything you need to know about that career path.
First things first – data engineer is just one of the most coveted data science job roles
out there, so keep in mind the other options, too:
data analyst; BI analyst;
data engineer; data architect;
and, of course, data scientist.
We’ll post a video just like this one for each of these career paths – if you’re
interested, be sure to check them out.
So, who’s the data engineer, and more importantly, what sets them apart from everybody else?
Data engineers are the Jedi Knights of data science.
They rely on a blend of analysis, wisdom, experience, and judgment to make key decisions
for a company’s success.
A data engineer is a self-starter who is inspired to complete more than your usual number of
tasks.
What does that mean?
Data engineers are the ones to take things further up the data science pipeline.
They use the data architects’ work as a steppingstone and then preprocesses the available
data.
These are the people who ensure the data is clean and organized and ready for the analysts
to take over.
Data engineers also implement complex, large scale big data projects with a focus on collecting,
managing, analyzing and visualizing large datasets.
All that massive amount of overwhelming raw data?
Well, they are the ones turning it into insights using various toolsets, techniques, and cloud-based
platforms.
You might think that’s enough work for one day?
Not for the data engineer.
Data engineers are also responsible for building and maintaining ETL pipelines which make crucial
data accessible for the entire company.
And when they get a minute, they lend a helping hand to BI analysts by designing and supporting
BI platforms.
Who makes sure all big data applications are available (and performing properly)?
Again, data engineers.
And, to top it all off, they are great team-players.
A data engineer knows how to actively collaborate with data scientists and executives to build
solutions and platforms that meet, or even exceed a company’s business needs.
So how does all this responsibility translate into the data engineer salary?
We asked Glassdoor and PayScale to give you a good answer.
In the U.S., the average pay for a data engineer who’s just getting started in his career
is $103,000.
Of course, once you hit the 4-6 years’ experience mark, you can expect your compensation to
rise to $117,000 (plus, you’ll be eligible for additional bonuses in the region of $10,000).
Looking for a data engineer job in the UK?
According to Payscale research, even if you have less than 1-year experience, you can
get average pay of £30,000 (this includes bonuses and overtime pay).
Naturally, with experience comes a higher salary.
A data engineer with 1-4 years of experience earns an average total compensation of £41,000.
And it only gets better!
Once you have 5-9 years of experience, your annual pay can hit £54,000.
Big data, big rewards!
But what does it take to become a data engineer?
The data engineer path is one of the best choices you can make if you’re driven to
succeed in data science.
But what if you’re new to the field and you’re not sure you’ve got what it takes
to get there?
Don’t worry.
Here are the steps that will lead you to a data engineer career.
Let’s consider education first.
What academic background do you need to become a data engineer?
Obviously, a degree in software engineering, computer science, or information technology
will give you a flying start.
However, if that’s not the case, you can still make the cut.
But you still need skills in computer programming and software design, statistical modeling
and regression analysis, Python, SQL, and Machine learning.
Now, before you rush into writing off your dream job, you should know that acquiring
these skills is absolutely possible, even for complete beginners.
Today, there are plenty of qualification programs and online certificate data science trainings.
Once you complete the courses and gain experience with real-world exercises and projects, you
will have the skills, confidence, and the portfolio to apply for a data engineer position.
Next – let’s talk about skills and qualifications.
What do you need in this department to become a data engineer?
Well, as we mentioned, a data engineer job comes with certain (many) responsibilities.
So, here’s a list of competencies and skills you need to become a data engineer who knows
their stuff.
Technical skills…
For a data engineer, knowledge of data modeling for both data warehousing and Big Data is
a must, along with experience in the Big Data space (Hadoop Stack like M/R, HDFS, Pig, Hive,
etc.).
Of course, the ability to write, analyze, and debug SQL queries will help you score
high on any employer’s recruitment list.
One more hint – make sure you gain some experience with at least one scripting language,
for example – Python.
And don’t forget the basics – Mathematics is never out of style in the data science
competitive universe!
How about practical skills?
Nothing unusual, if you ask us.
That is, of course, considering you have the Jedi powers of data engineers.
So, young Padawans, focus on these you should, if to succeed as data engineers you want.
Hone your data visualization skills (make Tableau or PowerBI your best friend);
Analytical skills; Ability to make sound decisions, even
in the absence of complete information; You must make sure you follow through
on commitments and make sure others do the same;
Personal responsibility for decisions, actions, and failures;
Establishment of clear processes for monitoring work and measuring results;
Design of feedback loops into work; Strong attention to detail;
Ability to think critically and conceptually.
But it’s not all about what you know.
Soft skills are just as important, so…
You’ll need to develop very strong communication skills in a variety of communication settings.
That means more than a meet-and-greet in one-on-one meetings, and small and large groups gatherings
among diverse styles and position levels.
Okay!
Now you know what it’s like to be a data engineer and how to get there!
However, better preparation means higher chances of success, so if you feel like you still
need additional career advice and a more detailed analysis of the career opportunities in data
science – we wrote a very long article about this, and the link is in the description,
if you want to learn more.
Thanks for watching and best of luck on your journey towards data science!
In the meantime, if you liked this video, don’t forget to hit the like button, share
it with your friends, and subscribe to our channel!