Qualified support through data stewardship - a new approach to data steward profiles from Germany The concept of data stewardship as a support for researchers, but also as a field of research itself, is becoming increasingly important due to the overall growth in digital data volumes. Qualified employees are needed in (inter-)national data-infrastructure initiatives such as the European Open Science Cloud (EOSC) as well as the National Research Data Infrastructure (NFDI) in the German context as a national example. Also the requirements of research funders often prescribe professional data management. The demand for qualified personnel is high and will probably continue to grow. Although the term "data steward" is frequently and widely used, the tasks, roles or institutional embedding of data stewards remain ambiguous and are still not clearly defined. In other European countries, studies e.g. in the Netherlands and Denmark have already identified somewhat congruent profiles of data stewards. The poster presents results from a research project dealing with the German academic landscape with regard to Data Stewardship. On the one hand, the situation and needs analysis was carried out based on the relevant literature and job advertisements as well as qualitative interviews. Furthermore, the poster shows the results of focus group discussions held with different stakeholders to derive recommendations for action. The central finding the poster presents is that there is no universal way to implement data stewardship. Instead, the implementation of data stewardship is highly depending on the local conditions. The poster proposes a change of perspective, describing different models of data stewardship based on the capacities and needs of the institution. Specific teams of data stewards can be assembled in a modular system. Five data steward profiles are available for building data steward teams, based on six dimensions: (i) the size of the research institution, (ii) the institutional location, (iii) basic knowledge of research data management, (iv) the need for specialised knowledge, (v) the breadth of the range of tasks, and (vi) the need for service orientation as opposed to scientific, research activities. Based on different combinations of these criteria five profiles of data stewards are described, such as the data steward as a generalist at a service point in a small research institute with a broad range of tasks. As a counterpart to this, the scientific working data steward in a collaborative project with specific expertise who works closely with the researchers on a research question has emerged. Besides the proposal of a modular system of data steward profiles the poster claims a need for further research on the quantitative demand for the specific profiles. Based on this, suitable training capacities can be build aligned with the specific demand for data management experts.