Job Details

Python Developer at Yandex to work on the Yandex DataLens service. Tasks include API development, connectors, scaling, and open-source core development. Hybrid work format.

Build a flexible API for data analysis tasks, optimize the construction of the data model. Datasets are a way to combine a large amount of data into a model that, regardless of the data source, allows querying it through a universal API. Datasets must work quickly with any number of fields: this is achieved through various optimizations and several caching levels. In addition to developing the dataset API, we are also enriching the service with other features that improve the user experience (e.g., exports, alerting, public API). Develop connectors to connect to new sources. We are constantly expanding the set of available data source connectors to cover more analytics scenarios. The task of connecting each new source is unique in its own way: it is necessary not only to understand the intricacies of its operation but also to consider the interaction with the connector from the user's perspective. Work on scaling, stability, and performance of the service. Our team is responsible for all stages of the service lifecycle, from design and development to deployment and maintenance of all environments. We maintain both DataLens within Yandex – one of the largest installations among similar tools – and DataLens in Yandex Cloud – the largest cloud analytics and visualization service in Russia. Optimizing CI/CD pipelines, improving monitoring tools, developing diagnostic tools without direct access to installations and user data – there is always room for relevant infrastructure tasks in our plans. Develop the service core in open source to unlock new possibilities for its expansion. To allow anyone to add new connectors or other functionality to the service, to assemble and configure the system according to their requirements, it is necessary to maintain and develop a modular code architecture: extract common parts, providing extension points.

Developed in Python or ready to switch to it from another language Worked with relational databases Built and maintained fault-tolerant systems