What Traits Make a Good Data Architect?

A good data architect is a gift to their organization because they achieve results that advance an organization’s data maturity. What kinds of characteristics lead to a data architect being considered good to great? One of the first traits needed is attention-to-detail. Many tasks that fall under the data architecture umbrella may have very repetitive and tedious aspects. Remaining focused and seeing tasks through to successful completion is not something “just anyone” can do. Attention-to-detail also means knowing what needs to be done. And for a new task not previously done by the data architects, then clearly they all need to learn it; and once taught, a good data architect pays attention to that as well. They likely shouldn’t need to be told the same thing more than twice. Along with this, a good data architect is self-reflective enough to know what they don’t know and should seek out ways to fill in any gaps as needed to accomplish the task at hand. Their attention-to-detail drives a level of persistence to see a task through, and a thoroughness of thought to expand beyond the wording of the given task. They understand the intent well enough to handle related items needing to be addressed at the same time. And all of these things, of course, without falling into sink wells requiring excessive amounts of time and effort beyond the intentions of the original task.

Curiosity is a good trait for a data architect. It drives data architects to keep learning new aspects about their profession. Curiosity also encourages data architects to be more proactive about their work. People with this trait are often considered people who never make mistakes. The truth is quite different, everyone makes mistakes. The proactive, however, are often able to be the ones who find and correct their mistakes before others notice. The curious and proactive also try to apply new knowledge to optimize processes, or even automate some of the previously mentioned tedious tasks. These individuals are often ahead of their managers by not waiting to be told to address obvious issues. When an issue is brought up, they can provide plans that they thought through on how the issue can be addressed.

Communication is critical; but being technically advanced yet suffering from a severe lack of social skills is not a great fit for the data architecture world. It is not unusual for a data architect to have to fill the role of a business analyst pulling information from the minds of business staff or needing to step up into a teaching role across IT or even business teams on data-related issues. A good data architect can explain, teach, and cross-examine witnesses. The other side of this coin is that a good data architect also listens well. They do not force their views in a one-sided fashion.

A positive attitude is always a plus. But if everything else is present within an individual then one can cope with a less than positive attitude (cope with, not necessarily embrace). There is a fine line between being a curmudgeon and being toxic, so it’s crucial to be alert and stay on the proper side of that one. Data architect tasks can vary greatly from organization to organization, or within data modeling, tool evaluations, data mapping, data flow diagramming, ETL tasks, SQL optimization, data archive design, even a little data strategy, and more could be included. But while tasks (and related priorities) vary greatly, the qualities that make someone successful and valued in a data architecture role remain fairly constant. Hire well, and when you do so then make sure you step up to the task of being a good employer.