Almost all professional figures working in IT participate in the data management processes during the data life cycle. And not only them. Business figures are also increasingly involved in the organization’s data asset governance activities. Data Management Body of Knowledge (DMBoK®2), a fundamental manual for data professionals published by DAMA, the international association of reference in the field, provides a complete and clear picture of jobs related to data.

Some professional roles are directly involved in data management activities, as in the case of Data Architects who define the technical standards for data management, classification, integration, and encryption and participate in their implementation. These standards guarantee an adequate level of smoothness in data streams and ensure system interoperability. Others are involved indirectly, for example, Web Designers and Web Masters.

But what are the key data jobs that DAMA indicates? What are the data-related positions in demand on the market, especially by companies that have already taken the way of organizational changes to become data-driven?

Executive and Business Roles: from data to decisions

Starting from the top positions in the organizational chart, the so-called C-level, being aware of the enabling role of data for enterprise value and the necessity to develop and foster data culture is an increasingly required quality among the Executive profiles, both on the IT and the business side. At this level, the position most directly involved in data asset governance is the Chief Data Officer (CDO), increasingly present in large enterprises.

Some high-profile business figures have formal accountability over a dataset, although data asset management is not their principal task. Thus, their responsibilities include those of a Data Owner role.

At the more operational level, Data Stewards have competencies in a specific information field and collaborate with business process analysts to ensure the smooth functioning of business processes.

IT roles: the indispensable technical supervision

There are increasingly many business roles related to data. However, the more traditionally data-related profiles that DAMA indicates are on the IT side. Let’s start with the already mentioned Data Architect. This figure pays attention to the logical and business aspects concerning the data and its adequate technical management, ensuring a high level of flexibility, smoothness, efficiency, and quality of the corporate information system. Data Modelers also play a key role in this field. They use specialized techniques and tools to formalize logical and physical data characteristics and its interrelations both within the perimeters of specific information areas and at the entire business data asset level. Other crucial roles for the correct technical system functioning are Database Administrators and Data Engineers. The former are responsible for the technical management of structured data archives, while the latter are engaged in the implementation of data integration and preparation processes, especially for analytical purposes. In addition, Security Officers and IT Auditors address, supervise, and control other IT aspects.

Hybrid roles: the connecting figures

There are some roles whose positioning within an organization may vary from case to case. For example, the characteristics of the Data Quality Analyst figure are a mix of technical skills and business knowledge. This specialist designs data quality rules and manages their execution, besides being involved in continuously improving data reliability. Besides, we cannot but mention the category of data analysis specialists. We speak of Business Intelligence Analysts and the most demanded figure on the market – Data Scientists. They specialize in using advanced analytics techniques, artificial intelligence, and machine learning to extract as much value as possible from business data. Finally, we highlight the figure of Information Designer, which is becoming increasingly relevant due to the ability to make it easy to interpret data analysis results thanks to the advanced visualization techniques. Still, the list of data jobs is clearly much broader and continues to evolve.