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!
