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Cloud Engineer vs Data Engineer - Which Career Path Should You Choose? | Luiz Roth | YouTubeToText
YouTube Transcript: Cloud Engineer vs Data Engineer - Which Career Path Should You Choose?
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This content compares Cloud Engineering and Data Engineering roles, highlighting their distinct responsibilities, essential skills, and career prospects, particularly in the context of AI development and industry layoffs, ultimately recommending Cloud Engineering as a foundational career path.
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Cloud engineer versus data engineer.
Which career path should you choose?
We've seen non-stop rounds of tech
layoffs and fear is spreading across the
industry. Most of these layoffs
companies claim are because of AI and
big cos like Sam Ottoman keep saying AI
will eventually replace jobs non-stop.
But here's the truth. Both cloud
engineers and data engineers are the
ones who actually make AI possible. Data
engineers create usable data to feed AI.
Cloud engineers build an infrastructure
that allows AI to run live at scale. So
what's the difference? Which career path
fits best for you? And most importantly,
what separates those who thrive and stay
in high demand from it pros who risk
becoming outdated like legacy code in
old citizens. Hi, I'm Lois Roth, a
senior cloud engineer with over a decade
of experience in tech and mentor helping
professionals futureproof their careers.
And by the end of this video, I will
show you exactly which path to choose
based on your goals and today's market
reality. Before we break down the key
differences, let's start with the
similarities. Both roles rely heavily on
cloud platforms. Whether it's Microsoft
Azure, Google Cloud or AWS, you need to
choose one to specialize in. Inside
these platforms, there are hundreds of
services and past tools. Somes are
uniques to each role while others are
shared but used with different goals and
at different levels of depth. So let's
start by looking at what a cloud
engineer does. Cloud powers almost
everything you touch online today.
Whether you are chatting with chatty
GTP, scrolling YouTube, or streaming
Netflix, it's all running carefully
designed cloud infrastructure hidden
behind the scenes. Before the cloud,
companies relied on their own servers
stacked in data centers. It was
expensive, is slow to adapt, and when
the main changed, servers crashed. If
traffic dropped, money was wasted on
idle hardware. The rise of the public
cloud flipped that model on its head.
Now business can simply rent computing
resources from platforms like Asure, AWS
or Google Cloud. Need more capacity? You
scale instantly. Less demand, scale down
and stop paying. It's efficient, it's
flexible, and reshaped the entire tech
industry. And the people who make that
happen are cloud engineers. Every
business from government to banking and
to health care is racing to the cloud.
Yet more than 70% of enterprises still
depend on legacy systems and over 8%
operate in hybrid model. This complex
challenge requires skilled cloud
engineers to design secure, scalable and
seamless solutions. So what do cloud
engineers actually do daytoday? As a
cloud engineer, you will work with Azure
or other cloud platforms from the ground
up. You will manage virtual machines,
not just turning them on, but
understanding how they connect, how to
secure them, and how to keep them
resilient when failures happen and
demand increases. You will work with
blob storage. It may look simple, but is
the backbone of storing unstructured
data at scale. From files to backups,
you will manage containers, control
access, ensure data stay secures,
durable and highly available. You will
design virtual networks. This is where
everything connects. Subinets, routing,
and security rules to make systems
communicating safely, efficiently, and
with high availability. You will run
security and identity management
defining access with rolebased access
control enforcing zero trust principles
and safeguarding work of loads across
the cloud. Once the foundation is solid
you will tie everything together with
infrastructures as a code using tools
like Azure bicep or terraform to
automate and keep environment
consistent. From there, you will build
pipelines with Azure DevOps or GitHub
actions to push applications into
production quickly and reliably. But the
role goes beyond technical work. Cloud
engineers collaborate across teams,
align with leadership, and translate
business needs into practical, scalable
solutions. They sit at the intersection
of technology and strategy. That unique
mix of technical expertise and
communication makes the role
irreplaceable for any modern business
and salaries reflect that. Cloud
engineer salaries typically range from $110,000
$110,000
to 106 with senior engineers and
architect roles often reaching $170,000
to $200,000 at the top end. That's why
cloud engineering is considering one of
the most futureproof careers in tech.
Now let's look at the other side. Data
engineers. Every AI model, every
dashboard, every business report you
ever seen depends on one thing. Clean,
reliable data. Without data, there is
nothing to analyze. Without structure,
there is nothing to build on. That's
where data engineers come in. Instead of
managing servers and infrastructure,
your focus is on data pipelines. You
take raw massive data from logs, apps,
customer transactions and clean it up,
joining it with other resources and
making it consistent. You design systems
that move this data reliably whether
through realtime streams or large scale
batch jobs. You build and manage
databases, warehouses and lakes, places
where massive volumes of data can be
stored. Even generative AI relies on
this work. Splitting documents,
embedding, storing vectors. It all comes
down to data pipelines. Agent AI, same
story. Tools must connect, data must be
clean, logs must be tracked. Even
dashboards showing live business metrics
depends on data engineering to ingest
strings, aggregate fast, and stay within
service level agreements. The role is
highly involved with numbers, often
requires advanced coding skills, and
appeals to people who enjoy working with
ambiguity and solving data problems at
scale. Data engineers also can earn
competitive six-figure sellers, usually
around $100,000 to $150,000.
So, how do these two rows compare? Both
are futureproof. Both are well paid.
Both are essential for AI modern
business. Cloud engineers build the
infrastructure, the systems, the
networks, the security that everything
runs aligned with business goals. Data
engineers build the pipelines, the
cleaning, the storage to make
information usable so business can make
smarter decisions. Take Azure blob
storage. A cloud engineer uses it mainly
for hosting application files, VM discs
or backups, making sure it's secure and
cost efficient. A data engineer on the
other hand relies on its as a data lake
dumping raw data sets feeding them into
pipelines or machine learning models. Or
look at Azure SQL database. A cloud
engineer might provision configure
secured and manage backup. A data
engineer uses SQL daily cleaning joining
and transforming data into something
usable for analysis or reporting. Now
consider Azure datab bricks and
Microsoft fabric. A cloud engineer sets
up environment, manage networking and
integrates identity. Identity engineer
spends their time inside running
analytics and turning raw inputs into
insights or features for machine
learning. So even though both roles
touch cloud platforms, when you compare
the two, the difference becomes clear.
Data engineering is more analytical. If
you enjoy problem solving at the data
level, coding and like the idea of
cleaning and shaping information
insights, data could be a good fit.
Cloud engineering on the other hand is
about building infrastructure. It's less
about complex algorithms and more about
systems thinking. You still code, but
it's not as heavy as in data pipelines.
If you prefer building environments,
managing systems and focusing on
scalability, security and even
interacting with stakeholders, cloud is
better choice. Now, if you're still
trying to decide which one to pursue,
here's my recommendation. Start with
cloud engineering. Here's why. Every
company needs the cloud. Whether or not
they adopt AI, whether or not they build
advanced data systems, cloud
infrastructure is backbone. the demand
is broader and the skills transfers
everywhere. Then once you're confident
in cloud, you can always add data
engineering on top to upskill. That
combination makes you extremely
valuable. The kind of engineer companies
compete to hire. And if you want a
proven road map to get there, check out
the link in the description. Enjoy my
program, the cloud career launchpad.
It's packed with everything you need to
go from zero to confident job ready
cloud engineer. From cloud fundamentals
to real world projects to interview and
positioning strategies that actually
work to the soft skills required
specifically for cloud engineers. So if
you are aiming for a six-figure career
in tech, this could be your chance. And
before you go, don't forget to hit like,
subscribe, and share this video with a
friend who needs to hear it. I will see
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