Main image of article Data Architect Skills: What You Need to Succeed

Data architects are among the more senior members on a data team, with years of experience working with multiple types of technologies. They have a strong understanding of data warehousing, data management systems and data modeling, and they use those abilities to help organizations build out their respective data architectures.

Their technical skills may vary based on the types of systems their organizations use, but all data architects have the same fundamental skills. Let’s break down what you need to learn to become a data architect in today’s environment.

What do you need to know to become a data architect?

Pranabesh Sarkar, senior distinguished architect, data architecture, engineering and governance at Altimetrik, suggests that both technical and soft skills are key for designing an effective data platform.

"A data architect has many responsibilities, starting with understanding the business requirements and converting the same into a pragmatic and scalable data infrastructure," he says.

That means a data architect needs to be well versed with different database solutions, including:

“They need in depth understanding of various NoSQL types and skills to apply the right one for a specific business problem,” Sarkar adds. “Hands-on experience with a variety of data solutions along with data modeling is a must-have skill.”

Sunil Kalra, associate director of data engineering at LatentView Analytics, says it is highly recommended for data architects to have experience with at least one public cloud analytics service such as:

“These cloud platforms provide a wide array of analytics tools and services that can be leveraged to extract meaningful insights from data,” he says. “Overall, possessing these skills and knowledge is essential for data architects to effectively navigate the complexities of data architecture in today's data-driven landscape.”

How can I train to become a data architect?

With new technologies and trends constantly emerging, data architects must be at the forefront of whatever is coming next. That means a life of continual education and training.

“Every year technology will change—last year it was moving to the cloud, this year it’s Snowflake,” says Jim Halpin Jr., technical recruiting leader for LaSalle Networks Chicago. “Data architects have to be able to take the initiative to learn the new technologies.”

From his perspective, the best data architects are also never too far from the code and regularly participate in code reviews and audits, keeping a pulse on the specific KPIs in their environment. “They enjoy the technical side, as well as the big picture strategic thinking, and so oftentimes they have an idea where the trends are moving and spend time researching, reading and discussing those topics within their network,” he says.

Beyond networking, conferences, meetups and publications, there are also structured programs including certifications, master's programs and bootcamps data architects can participate in.

“Azure and AWS have certifications, there are master’s programs in predictive analytics and so many more,” Halpin says. “Most data architects choose what’s most relevant to their roles.”

Here are some online training programs that can help you learn the intricacies of the data architect career track. Keep in mind that some of these options are quite costly, while others (such as YouTube) are cheap or free:

Evaluate any course carefully to make sure it meets your needs and timetable before beginning.

Do you need a degree to become a data architect? Or just skills?

Given the demand for skilled data architects (and the historically low unemployment rates throughout the tech industry), you don’t necessarily need a formal degree to become a data architect, so long as you can convince a hiring manager and/or recruiter that you have the necessary skills for the job.

Keep in mind that any data architect job interview will plunge deeply into your technical experience, with your interviewer asking several questions to gauge your aptitude and experience level with various tools and platforms. For example, you’ll be asked:

  • Your experience with building out data models.
  • How you’ve ensured data security and integrity when building and managing databases.
  • How you manage external data sources in relation to a database.
  • How you’ve overcome challenges and secured buy-in from stakeholders when planning data architectures.
  • Whether you’ve transitioned datasets from on-premises to the cloud, and how you overcame challenges related to that.
  • Your methods for testing data architectures before release.
  • How you’ve applied strict data governance.

Those are just some of the questions you could be asked; the key is to stay flexible and come prepared with stories that put your skills and experience in the best possible light.

Data architects must also know how to talk business

A data architect must constantly work with different stakeholders in an organization, including the technology team, product management team, and business stakeholders. This means stakeholder management is a key aspect of the data architect profession.

Sarkar says every data platform in an organization is built to drive multiple business outcomes, noting the data architecture needs to be designed to handle multiple personas and different use cases. “It is important to engage with business teams before the design is initiated to understand the various requirements and expectations,” he explains. “It is advised to approach the solution in an incremental way by incorporating the business use case as part of the data architecture.”

A data architect must multi-task and troubleshoot multiple complex issues with data architecture. “To succeed, data architects must have a business-oriented mindset with a good understanding of the company objectives and goals,” Sarkar says. “The data architect is instrumental in using technical expertise to minimize platform costs while still delivering performance and scalability.”

Halpin adds that communication and collaboration are crucial skills for a data architect, as they often serve to bridge the gap between the technical teams and business leaders. “Data architects must have strong business acumen and a solid understanding of the direction the leadership team wants to take the company,” he says. “They are included in larger management discussions and their input is highly valued.”

This means they know how to tactfully present obstacles and challenges, as well as ramifications of decisions—both to leadership and the technical user. 

As Halpin points out, sometimes data architects are aligned to a specific industry and have deep subject matter expertise in that space: “We see this more in highly regulated industries like healthcare, insurance or banking where there is a lot of compliance and nuances that come with those fields.”

Other skills include project management, enabling data architects to plan, prioritize and execute ideas on time and on budget. “High levels of initiative to research emerging trends in technology, and strong communication skills to communicate ideas to leadership, as well as get in front of issues and manage expectations of both technical teams and leaders,” Halpin adds, are likewise critical.  

Staying up to date with emerging technologies is crucial in a rapidly evolving technical landscape. “Continuously seek information online, follow industry-leading companies' blogs and newsletters, and actively engage with new technologies through hands-on experiences,” says Kalra, who also recommends maintaining a habit of writing blogs to help stimulate critical thinking, encourage further research, and facilitate continuous learning.