One of the most promising careers within the data science world is that of data architect.
Data architects harness the power of data to make informed, accurate decisions that help them find long-lasting solutions to a wide variety of business challenges and problems. They can work in many different industries, including (but not limited to) healthcare, finance, entertainment and government.
What is a data architect?
Data architects are information technology (IT) specialists who define policies, procedures, models and systems for collecting, organizing, analyzing and storing company information.
Their exact duties and responsibilities will vary per position and per company, but there are some day-to-day responsibilities you can expect in just about every data architect’s role.
Some of these duties include:
- Creating and optimizing systems to ensure data accuracy
- Implementing data management procedures
- Analyzing data architecture frameworks (such as meta-data and master data)
- Developing application programming interfaces (APIs) to better collect data
- Collaborating with IT teams to improve data strategies and processes
- Designing and deploying database architectures and applications
- Monitoring and refining the performance of data management systems
As a data architect, you’ll be expected to have a high-level knowledge of technical architecture, such as database structures and management, operating systems and programming languages .You can refine data science skills through ongoing training, including participation in a data science bootcamp.
Why are data architects so important?
Without data architects to create and maintain data management policies, companies around the world would be left without ways to collect, assess and learn from their own data.
It’s a data architect who defines business strategies, organization and key processes; they optimize the entire structure of all data resources; they design and provide the blueprint for each system’s function.
Data architects are responsible for maintaining the technical infrastructure of an organization, as well as keeping all collected data secure, organized and efficiently distributable whenever and wherever needed.
How do I become a data architect?
Becoming a data architect can take time. As a higher-level role in the data science world, data architects need to hold a bachelor’s degree, accrue work experience, earn professional certifications and enroll in ongoing training.
1. Have a bachelor’s degree in a data-related field
While there are plenty of career paths within the data science field where a university education is optional or downright unnecessary, it’s a bare minimum qualification requirement for this position.
To be a data architect, you need to have a bachelor’s degree in either computer science, computer engineering or a related field. To attain higher-paying, senior-level data architect positions, some companies also expect (or at the very least, prefer) candidates to have a master’s degree with at least a few years of experience in a niched sector.
2. Figure out what kind of architect you want to be
There are different kinds of data architects, the most common of which are machine learning architects (AI-focused), cloud architects, security architects, and, of course, data architects.
It’s okay if you’re unsure of which position you want to pursue right now. Depending on your unique career vision, your professional wants and goals, you’ll quickly discover that certain roles are better suited to your skill set and career preferences than others.
3. Gain work experience
Whether through an internship or apprenticeship, you’ll want to gain as much experience as you possibly can in order to prepare for a data architecture role. There’s a good chance your first job title isn’t going to actually be “data architect,” as these employees typically have at least 3-5 years of experience on the job with multiple proven projects under their belts.
4. Earn professional certifications
You don’t technically need a certification to land a promising career in data architecture, but going the extra mile to receive additional, ongoing training will help catch the eye of employers.
By earning professional certifications from industry-recognized vendors or respected data architecture groups, you significantly bolster your knowledge, skill set, resume and earning potential.
5. Enroll in a data science bootcamp
Pace specializes in top-tier data science education that’s designed to equip aspiring data scientists with all of the knowledge, skills and training they need to pursue a rewarding, lucrative career in data science. We offer a data science program that’s already tailored to students who want to find accelerated, long-term success in the field.
Pace’s top priority is your long-term success. That’s why we’ve created a Data Science Bootcamp that connects aspiring data professionals with all the tools, resources and skills they’ll need to thrive in the professional world — without the cost of a four-year college degree.
Contact our Solutions team today to get started.
