Now the issue of basic digital transformation is very acute – the transition from a monolithic to a microservice architecture, to hybrid models that are constantly changing. For such companies, the issues of data normalization and management are of paramount importance, as well as the constant management of their integration flows. And this is where the market demand for specialists of a different kind stems.
The IT sector needs
- System and integration architects who can build intersystem interaction not at the level of classic ESB buses, but at the level of an API-centric architecture with changing relationships.
- System analysts who can shape, implement and describe the implementation of this architecture, stretch it in the ever-changing IT landscape.
- Strong project managers who will be able to organize teams to accomplish these tasks and manage communication processes at the client-developer level.
- System engineers who will be able to rebuild the infrastructure from the current monolith into a permanent hybrid and try new technologies.
- And since the alignment and normalization of all these processes is primarily associated with product information and information about services, then on top of all this variety of professions, category “data analytics consulting” stands apart – specialists who can build the right product models, enrich them depending on the context and user experience.
- Data Scientist. In other words, a data explorer. A specialist who works with large amounts of data, analyzes them, draws and visualizes conclusions. The main task is to find new patterns in the data and build a predictive business model. A simple example is to calculate how many materials you need for production. The data scientist’s tools include mathematical statistics, principles of logic, machine learning algorithms, programming base, probability theory, etc.
- Information security specialist. More beautiful – Information Security Analyst / Engineer. The profession is complex, specific, requiring a huge amount of hard skills and non-trivial thinking. But this is the future.
- Data Analyst. Unlike a data scientist, who are more involved in the “shadow” technical side, such specialists focus on the business component, that is, they solve specific business problems. The analyst studies the company and its needs, identifies problems, tests hypotheses and proposes scenarios for action. This implies a higher rhythm of work and active communication with stakeholders. In their work, they use programming algorithms, various libraries, data processing systems, mathematical statistics, etc.
- DevOps Engineer is a person who works at the intersection of many directions and brings together all parts of the project: a little programmer and system administrator, with knowledge of the nuances of testing and the entire business part. This specialist seeks to save the resources of its customer and for the sake of this it speeds up and automates the fintech software development as much as possible. The profession is relatively new, involving knowledge of a large amount of methods, tools, technologies and a desire to simplify and optimize everything.
Steady growth begins in digital production professionals. This is the implementation of CAD, CAE, PLM, etc. systems, including industrial robots. The growth in demand for this area was driven by two key factors. The first is the pandemic, which has directly shown that the level of digitalization of a company is a serious advantage, and sometimes a way of survival. The second is the need to dramatically increase the productivity of employees. The reason here is the economic crisis and the desire to reduce dependence on the number of personnel.