Digitalization processes bring about radical transformations in the content and nature of work, leading to shifts in the demand for certain skills and abilities and the emergence of new occupations. Traditional survey-based sources of information about the labour market prove insufficient to track these changes for employment policy purposes. In this article, the authors reveal alternative data sources on the labour market, made possible due to the development of new digital technologies, and delineate their respective advantages and drawbacks. Additionally, the authors systematize international experiences in leveraging digital technologies and Big Data for statistical and information-analytical research on the labour market. Having analysed the leading research-analytical projects in the USA, Great Britain, and EU countries, the authors found them to be focused on constructing functional intellectual and analytical systems for the labour market. These projects aim to develop methodologies and promote widespread adoption of digital tools for working with Big Data, significantly expanding the capabilities of labour market information and analytical systems. The authors examined specific projects that used Big Data from online job vacancies to assess the demand and supply of jobs, as well as to analyse and forecast the requirements for skills and competences that would be feasible for adoption in Ukraine. Big Data from specialized online portals, servers and services were found to serve as powerful resources to supplement and enrich the existing conventional system of labour market statistics and analytics. Finally, the authors substantiate the need and expediency of creating a fundamentally new Labour Market Information and Analytical System (LMIAS) in Ukraine and coordinating it with labour market platforms in EU countries. They also identify a range of problematic issues that require in-depth research and resolution in Ukraine, such as ensuring the representativeness of online job vacancy data, improving the classifiers of occupations, abilities and skills, and introducing methods for integrating statistical, administrative, and Big Data on the labour market.