Lead Data Engineer

Responsibilities:

• Design and development of scalable data infrastructure (batch and streaming pipelines);
• ClickHouse (MergeTree), S3 Data Lake, Kafka, Airflow (ETL/ELT);
• Architecture and implementation of data marts for analytics, ML, and AI agents;
• Support and development of ETL/ELT pipelines (dbt / Airflow / Spark / Kafka / etc.);
• Optimization of performance, data storage, and consumption costs;
• Implementation and support of CI/CD standards and pipeline monitoring;
• Collaboration with analysts, ML engineers, developers, and product managers;
• Participation in building feature stores, ML infrastructure, and supporting GenAI systems.

Candidate Profile:

• 3+ years of experience with data in a Data Engineer role;
• Experience in designing production data platforms (from ingestion to data marts);
• Excellent knowledge of SQL, Python (or Scala), experience with Apache Airflow, Spark, Kafka;
• Experience in building CI/CD processes and monitoring data pipelines;
• Understanding of data governance, data quality, and data contracts principles.

Will be a plus:

• Familiarity with MLOps practices and GenAI pipelines (e.g., RAG, LangChain);
• Experience collaborating with ML engineers: feature preparation, feature store support;
• Experience leading a team or individual projects as a technical lead.

Working Conditions:

• Stable employment in one of the largest banks in the country;
• Competitive salary, social package;
• Work format - hybrid (4 days in the office);
• Opportunities for growth and development (including conferences, trainings, internal development programs);
• Friendly team of like-minded professionals;
• Cutting-edge technology stack, high-performance equipment;
• Opportunity to solve diverse applied problems with industrial deployment, significant impact on results;
• Quarterly bonus based on performance;
• Voluntary medical insurance, life insurance;
• Corporate training.