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Jump start your future career with Google Cloud certifications

Ever since I published “Career tips and no-cost training for the next generation of cloud technology,” people have been asking me how to turn the trends introduced in the blog post into career growth. As I said in the blog post, these new ways that businesses are using the cloud come with the need for new roles and expanded ways of looking at existing ones. While many of the new roles are technology-based, you’ve probably already seen how cloud-based tools have made the way into non-tech tasks. And with the right cloud training and experience, your career advancement options can only widen.

To give you a better picture of how the cloud’s evolution is opening up new career opportunities, this blog will look at how the four key pillars mentioned in my previous blog are opening up specific opportunities. Hopefully, you’ll see a few opportunities that map to your ideal career path, and maybe even inspire new possibilities that will put you at the forefront of cloud adoption in your field.

Modern compute

When the cloud first started to become a thing, it was all about virtual machines and virtualizations. Not only did they change the way people worked, it got more businesses up onto the cloud with fewer disruptions and slowdowns. At that stage, just having any experience with cloud computing would have put you ahead of the crowd, but nowadays, most large companies are on at least one cloud, while startups have the advantage of never having to worry about physical infrastructure.

To meet the ever-changing future of compute, businesses are turning to containers and Kubernetes. By containerizing applications, they become more portable and easier to move from one place to another, all while making it easier to change and modify applications.

From a tech perspective, the most obvious roles this affects focus on app development. By understanding how containers work and how to make quick updates and adjustments to code, you will be much more ready to build for whatever shifts the app development space takes.  Even if you aren’t on the code side of app development, knowing how containers work can help you design app functionality that can grow with your customers’ needs.

This leads into the other major way modern compute affects your work: DevOps. No matter how technical your role is, the cloud and containers affect not just what you make, but also how you work. As containers become more common and plentiful, employers will need team members who understand enough about the architecture and ecosystem to optimize operational speed and capitalize on the additional flexibility while maintaining business continuity.

If you’re an engineer looking to use the cloud to strengthen DevOps, check out our Professional Cloud DevOps Engineer certification.

Polyglot database engines

Traditionally, when engineers thought about how to store data, they had to choose between relational and non-relational databases, meaning that they had to decide which benefits they were willing to go without when picking. Relational databases offered structured storage that worked better with tables, but they aren’t very flexible or scalable. If you needed to make any changes — even something as small as adding a new column — you were better off with non-relational databases.

With the rise of the polyglot database engineer, businesses don’t have to sacrifice as many benefits. By changing how we interact with data and how tools communicate with databases, you can store data for inventory while making it available for processing and analytics, all without moving it around too much. For example, you could federate a query from a relational data warehouse like BigQuery into a non-relational one like Spanner so you perform analysis and gain insights without disrupting the structure and integrity of the dataset.

Obviously, anyone who can manage these processes will be desirable, but just having a basic understanding of how different databases work with each other can help you do more in non-technical roles. Learning how to interact with relational databases will help anyone involved in data collection and storage, and understanding the potential of non-relational databases can get you to essential insights quickly, meaning you can act sooner with more informed decisions.

If you’re looking to strengthen databases with the cloud, consider checking out our Professional Cloud Database Engineer certification.


Artificial intelligence and machine learning are probably the most accessible aspects of the expansion of the cloud, whether your role is technical or not. Everyone seems to be talking about how AI will change the business landscape — in everything from documentation to predictive analytics — so just being able to prove AI/ML knowledge will be a huge benefit to any team and a great addition to your resume.

At the basic level, you should familiarize yourself with the ideas of how ML model training works and how generative AI opens this up. Feeding collected data into a model can return AI based on that data, but when the model takes this data and creates iterative generations of AI, you can get more accurate results with far wider functionality. Even the types of data these models can ingest and return are expanding — from language models that can do more with text to multi-modal ones that can deliver images, videos, and rich data content.

And as we’ve already seen from AI chat and image generation tools, even non-technical users can get amazing results — including examples of innovators like Khan Academy who are using AI to help students and generate lesson plans for teachers. As businesses integrate more ML into their operations, everyone from marketing to accounting will have to start exploring how to do more with AI. That means that if you already have a strong understanding of how it works, you’ll be ahead of the curve.

Of course, this also opens up many opportunities for technical professionals. ML engineers who can build these ever-larger AI models will construct the future of how their employers do work, so an AI/ML certification will be very attractive when you’re looking toward the next stage of your career.

At Google Cloud, we’ve been an early supporter of AI/ML, which is why we are proud to offer a Professional Machine Learning Engineer certification. If the data side speaks more to your career goals, you can also become certified as a Professional Data Engineer.

Multi-cloud and hybrid

While the future of business may be built on the cloud, organizations don’t need to just pick one cloud anymore. The growth of multi-cloud environments has driven interconnectedness between clouds, so now companies can choose the best clouds for specific segments of their operations with the assurance that they will all work together. And for businesses that have specific needs that require on-premise servers, hybrid cloud computing can link your physical infrastructure with the cloud tools you need.

This opens up the potential for businesses to use an ever-expanding array of cloud tools, so having a broad understanding of the various ways employees from across the organization can use these tools will make candidates far more attractive to recruiters. Just knowing which clouds work best with which aspects of your business and which might need on-premise storage can help drive efficiency and cost-savings.

For technical roles, the potential is more obvious, but beyond just architecting a multi-cloud or hybrid environment, knowing how these servers interconnect can help you maximize flexibility and security. The more servers data passes through, the more areas of uncertainty might arise, and while clouds like Google Cloud are designed with security in mind, demonstrating an understanding of how to maximize security throughout the system proves that you know what it takes to keep the business safe and running.

If you want to demonstrate an understanding of multi-cloud and hybrid cloud — as well as how they are currently and can potentially change the business landscape — take a look at our Professional Cloud Architect certification.

Building a more cloud-ready you

If you already see how the cloud can help you personally in your career path, your next question will likely be how you can start learning. I’ve created several blog posts and a book — “Visualizing Google Cloud: 101 Illustrated References for Cloud Engineers and Architects” — that offer great ways to start developing your learning path and prepare for certifications.

For more formal learning, Google Cloud offers an extensive range of training courses, hands-on labs and certifications.. Check out our learning platform Google Cloud Skills Boost, where you can get started with hands-on labs, role-based learning paths which offer training courses on a a wide range of cloud solutions. When you’re ready, you can also explore Google Cloud certifications in everything from the broad, foundational cloud knowledge through theCloud Digital Leader certification to specific certifications for a wide variety of technical roles, like Professional Cloud Architect or Data Engineer certifications. Together, these will give you the knowledge of the cloud you need to help you along your cloud career path.

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