Data Integration Career Architecture

Those who understand data integration and the supporting technology are in high demand. Why? The need to create data synergy within enterprises, among both traditional and cloud computing-based data and applications, is inflecting. This is due to a more clearly understood business benefit around the value of data integration.

The ability to have information arrive on-time and when needed has been a fundamental need of IT since I wrote the EAI book over a decade ago. However, in the last few years, systems became more complex, including the complexity of the data that exists within them. In response, data integration grew more complex, the technology more sophisticated, and thus the increase in the demand for data integration talent. 

It’s what I call “silent demand.” While the world seems to be focused on cloud computing and big data, the number of data integration jobs increased significantly in the last few years. For example, Figure 1 depicts the growth of jobs posting with the term “data integration” in them since around 2006.

Figure 1: Number of job descriptions citing "data integration" since 2006. Source: Indeed.com

However, defining yourself as a data integration expert is something that takes some thought these days. In other words, you need to create architecture around your data integration career. I view these as tiers, or graduated levels of expertise.

Level 1:  Understanding the concept.

When asked about specific technology, you’ve seen people respond to interview questions this way: “I don’t consider myself an expert, but I do understand the concept.” Fair enough. These are typically the people at the start of their data integration career who have read about data integration, but have never worked with it directly.

If you’re here, you need more experience. Join a data integration project. Most of them will be happy to have you, and to teach you.

Level 2:  Understanding the technology. 

These are people who have worked on some type of data integration technology in the past. While they understand the underlying technology, typically they don’t have a clear understanding of the architectural art of data integration, including how to deal with application and database semantics, governance, security, performance, etc.. Rather, they understand how to hook up data source one to data source two.

If you’re here, it’s time to get smarter around the academics of data integration.  This includes the process of creating data integration architecture, as well as dealing with various solutions patterns, such as data staging, data virtualization, or simple data replication.

Level 3:  Understanding everything. 

If you’ve reached this level you’re in very high demand. This means you understand both the architectural problems of data integration, enabling technology, and emerging solutions. You understand how SOA and data integration are linked, as well as how to drive a solution from the requirements to production.

Of course, you never stop learning, so these are also people who make time to attend relevant conferences and read all they can. These are highly valued employees, and can command generous salaries because of the value they bring to the business.

So, start your journey now. The need for great data integration talent will only increase as the technology improves, and the value is better understood.

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