Head of the DWH team for Alisa

Alisa is an AI assistant that entertains and simplifies everyday tasks. We have over five million users, and we are constantly working to make Alisa smarter and more helpful.

Every day we answer questions such as: * how successful Alisa's interaction with the user is; * whether we found the right song from TikTok; * how many requests a user needs to hail a taxi; * whether we succeed in telling users about Alisa's available features; * which user needs are still unmet, which questions we cannot answer; * how to define minimum quality requirements for launching a new feature; * how good our music recommendations are and how to assess their quality.

What tasks await you

Architecture design and requirements gathering You will develop the data warehouse architecture, including designing layers, flows, and data models. Furthermore, you will interact with business users and contractors to gather and clarify requirements for the DWH, select and implement basic technologies for ETL processes.

Implementation of data marts, data quality management, and access policies You will coordinate development teams in the process of DWH implementation, implement and develop data access management processes. You will also prepare technical and methodological documentation, ensure data quality monitoring, and implement tools for tracking incidents.

Development and support of ETL processes, improving data quality and stability Working as part of V-teams for your data domains, you will design and maintain ETL pipelines for data processing – from sources to dashboards. You will also ensure the stability and performance of data marts and dashboards, develop mechanisms for data quality control, and optimize existing processing processes.

Technical support for analysts You will become the primary point of contact for analysts on technical issues related to working with data and platform tools.

Team leadership and data platform development You will become a technical leader for the data engineers team: you will distribute tasks, monitor their execution, participate in planning and defining strategic directions for platform development. You will also need to implement standards and best practices in the field of data processing and storage, optimize workflows, and eliminate "bottlenecks" in architecture and data processing processes.

We expect you to

• Enjoy working with data and know how to extract practical results from it
• Know mathematical statistics and probability theory
• Write in Python and know algorithms
• Be independent and ready to take on new tasks for which there is no ready-made solution