We are a team that develops a client feedback platform and creates AI solutions for quickly extracting insights from surveys and requests. Our goal is to transform raw feedback into structured analytics accessible through an AI assistant and to shorten the path from client feedback to actual product solutions.
Responsibilities
You will:
- analyze the causes of data quality issues and interact with data source owners and consumers
- develop, implement, and support data quality metrics, rules, and standards
- design and implement ETL processes for extracting, transforming, and loading data from CSV/API
- optimize SQL queries (including window functions, CTEs, JOINs) and improve database performance
- participate in the integration of basic AI tools for processing and analyzing textual feedback.
Requirements
- higher education
- confident knowledge of SQL (window functions, CTEs, JOINs) and experience with PostgreSQL
- proficiency in Python at the level of working with pandas libraries and basic PySpark skills
- understanding of ETL principles: extracting data from CSV/API, transforming, and loading it
- knowledge of basic AI tools for data analysis.
Will be a plus:
- experience with the Hadoop ecosystem
- experience with stream processing (Kafka)
- knowledge of SQL syntax for Greenplum / ClickHouse
- understanding of task scheduler principles and DAGs in Airflow
- experience using GigaChat, Kandinsky and their analogues in products, skills in creating and using AI agents.
Conditions
- beautiful modern office
- office-based work format: Moscow, Kutuzovsky Prospekt, bld. 32, str. 1
- annual salary review and annual bonus
- over 400 educational programs at SberUniversity for your development
- gym and recreation areas
- expanded voluntary medical insurance, preferential insurance for family members
- free SberPrime+ subscription, discounts from partners
- reward for recommending friends to the Sber team.
