In this video, you’ll learn how to land one of the most promising jobs in data science.

Yes, we’ll tell you everything you need to know about becoming a data architect.

We’ll take a good look at who the data architect is, what they do, how much they earn, and

what skills and academic background you need to become one.

But before we get started, we’d like to quickly tell you about 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, so even if you don’t have any maths or statistics

knowledge, it will help you first build those foundations before moving on to more advanced

topics.

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.

So, 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.

Okay.

Let’s talk about the data architect career path.

First thing worth remembering – data architect is just of the most coveted data science job

roles out there, so here’s a list you should consider: data analyst; BI analyst; data engineer;

data architect; and, of course, data scientist.

We’ll post a video just like this for each of these career alternatives, so make sure

you check them out!

Alright!

Back to the data architect.

Who is the data architect exactly?

If you’ve seen the 1999 cult movie The Matrix, you probably recognize the Architect as the

creator of the utopian world for human minds to inhabit.

Much like their blockbuster counterpart, data architects create the database from scratch.

They design the way data will be retrieved, processed, and consumed.

That was the teaser trailer of the data architect job.

But what does the data architect actually do?

Data architects are technical experts who adapt dataflow management and data storage

strategy to a wide range of businesses and solutions.

They’re in charge of continually improving the way data is collected and stored.

In addition, data architects control access to data.

So, all you corporate spies out there – now you know who to look for.

Data architects are also responsible for design patterns, data modeling, service-oriented

integration, and business intelligence domains.

They often partner with fellow data scientists and IT guys to reach the company’s data

strategy goals.

A data architect constantly seeks out innovations to provide improved data quality and reporting,

eliminate redundancies, and provide better data collection sources, methods, and tools.

Hm…Sounds like serious business!

So, how much do data architects make?

We consulted with Glassdoor and PayScale to give you the numbers.

According to Glassdoor’s salaries report, the average annual pay for entry-level data

architects in the U.S. is approximately $104,000, while professionals with 4-6 years of experience

make more than $125,000 and can easily get bonuses in the region of $10,000 a year.

What about the UK?

As a data architect early in your career, you can earn an average total compensation

of £45,000.

However, a mid-career Data Architect with 5-9 years of experience can get as much as

£55,000, including bonuses and overtime pay.

It seems you can expect some solid growth!

That said, it’s time to answer the big question, which is: How to become a data architect?

If you’re now looking forward to starting a career as a data architect - Great choice!

The data architect role is on the rise with its increasing importance for enterprises

and their business success.

But there are a few key points you should take into account before you know for sure

that the data architect career path is the right one for you.

Let’s start with the academic background…

A Bachelor’s degree in information systems, computer science, engineering, or related

field will definitely give you a competitive edge.

But don’t be quick to despair if you’ve studied something entirely different.

It turns out, these are by no means prerequisites to get the job.

According to LinkedIn job offers, employers are much more interested in relevant work

experience than in shiny degrees.

In their own words, “Bachelor's degree in Computer Science is

desirable, but will waive this requirement entirely if you have significant and applicable

real-world experience.”

How can you get there?

First of all, master Python or R, SQL, Tableau, and gain experience in data modeling and machine

learning.

The good news is that even if you lack the qualifications, there are ways you can build

up your knowledge from scratch, be it by taking some additional qualification courses or by

enrolling in an online certificate data science training.

Speaking of qualifications, what are the data architect must-have skills you should acquire?

As a data architect, you’ll have plenty of challenges to solve daily.

That means you’ll need a robust skill set, including technical, practical, and soft skills.

We’ll review them here, but if you want to see the ultimate list, we’ve put a link

in the description to a super helpful article about starting on the data science career

path.

Okay – technical skills.

You’ve got to have some strong data modeling skills, experience in Python, R, and SQL,

and good command of data visualization tools, for example, Tableau.

Of course, you shouldn’t limit yourself to these.

That said, you can only benefit from some knowledge in XML and Java.

Then come the 3 Ds you should strive to add to your arsenal - Database architecture, Data

warehousing, and Data governance know-how.

And, finally, being familiar with data retention concepts and practices is definitely a plus,

along with understanding automation of data flows and integrations.

What about the practical skills?

Let’s take a look at the list of practical skills a data architect demonstrates.

So, a data architect can: lead multiple, highly complex efforts simultaneously; еstablish

and implement standards and guidelines; determine key architecture solutions that meet performance,

scalability, reliability, and security needs; research and evaluate emerging data management

technologies for applicability and adoption; present technical concepts to upper-level

management and officers; work independently; employ strong problem – solving skills;

execute tasks with impeccable attention to detail.

Anything else?

Yes - the soft skills.

Although there’s nothing out of the ordinary here, soft skills are sometimes the hardest

to master.

So, make sure you work on your communication skills and the ability to provide technical

leadership and guidance to your project team when necessary.

Alright!

Now you know the essentials of the data architect job and what skillset you should build up

in order to become one.

Thanks for watching and best of luck on your data science journey!

Meanwhile, if you liked this video, don’t forget to hit the like button, share it with

your friends, and subscribe to our channel!