The Present and Future of Data Management Roles

Orinal source post by Kevin Kline

In January 2015, I wrote about the future of professional database administrators (DBAs) in a three-part series of articles for Database Trends & Applications magazine. Back then I predicted we would see strong growth in DBA salaries because of the acute and persistent shortage of talent, very little means of training new DBAs, and a median age of DBAs creeping closer to retirement age with each passing year. It was a simple prediction boiling down to “When supply goes down and demand goes up, prices rise”. As with many predictions, I was right in some ways but wrong in at least as many ways.

One aspect of the supply and demand analogy I missed: Another answer to limited supply is simply finding alternative suppliers. This is what we’re seeing today. Activities traditionally managed by DBAs have started to splinter off into entirely new professions, with their own distinct processes, priorities, and tools.

I think this is such an important emerging trend that I’ve asked my friend, Bob Ward , to discuss the topic with me in a webcast later in November. As a preview of that conversation, let’s talk about today’s world of data professional careers. Here’s a quick rundown of career categories:

  • Data Management– Data and database management is still the realm of the professional Database Administrator (DBA) and a new title called Database Reliability Engineer (DRE). Older divisions in the role, such as “operational dba” and “development dba” are now much less common, although they are not completely out of use.
  • Data Integration– The last decade has seen a rapid rise of many SaaS business products sold by powerhouse ISVs such as Marketo, SalesForce, and ERSI. Many organizations have found that, while these products provide great business value, they also need specialized IT talent called Database Engineers to manage extract and move data between their on-premises databases, various SaaS providers, and their data lakes. These data integrations are usually called data pipelines.
  • Data Analytics – This domain involves business analytics, usually analyzing data from data warehouses and data lakes rather than directly from a relational database. In the previous decades, this domain was called business intelligence. Specialists in this domain may focus on the backend, designing data warehouses, data lakes, or front-end visualizations using platforms like PowerBI, Tableau, or AWS Quicksight. Titles in this career path include Business Analyst and Business Intelligence Architect.
  • Data Science – This career path incorporates an economist-like construction of predictive models, the application of advanced statistics to big data sets, and machine learning (ML) to automate the iteration of variables within their models, all in the interest of creating reliable descriptors or predictors of important business scenarios. Titles in this realm include Data Scientist, ML Engineer, Data Analyst, and even Data Storyteller.
  • Data/Database Architecture – Those who design database systems and applications, such as architecting the infrastructure and making architecture diagrams. Duties in this realm also include data modeling. Consequently, you might see titles like Database Architect or Data Modeler.

I chose to lay out career paths for data professionals by their domain because the domains are much more stable over time, generally speaking, than the job titles common within a given domain. On the other hand, the job titles I’ve mentioned are not fixed, have an ever-changing list of job duties, and may change or fall from favor in the future. Also, some titles may overlap and have more or fewer responsibilities based on the preferences and idiosyncrasies of the organizations that employ them.

Having laid the groundwork for our future discussion, I encourage you to join me and Bob Ward for an in-depth discussion of the deeper duties of titles in our upcoming webcast. I hope to see you then!

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