Data Engineer

The project focuses on the development of modern applications using generative artificial intelligence and large language models in a production environment. It includes the design of the AI solution architecture, their integration into backend and frontend systems, and optimization of performance and scaling. The development takes place in a small agile team with an emphasis on best practices (testing, CI/CD, code review) and practical use of AI for real business scenarios.

The work also includes working with prompts and debugging models, creating chatbots or assistants, and implementing APIs and cloud services so that the AI solution works reliably and long-term in production.

• Data solution development:
  Building robust data pipelines mainly in Python and Spark.
• Cloud & Modern Stack:
  Working in Azure and GCP environments on modern Data Lake platforms.
• MLOps in practice:
  Deploying, managing, and orchestrating ML models in production.
• Variability:
  Possibility to work on both rapid pilot projects (R&D) and stable long-term systems according to your preference.

• Strong experience with Python development.
• Practical knowledge of Spark and Databricks.
• Advanced SQL and experience with RDBMS.
• Cloud orientation (Azure or GCP).
• English at B2 level (for communication with global clients).

• Experience with modern SaaS (Azure Fabric, Synapse, Dataproc).
• Dev Ops overlaps (Terraform, CI/CD, Docker/K8s).
• Great colleagues and fully flexible working policy
• Career coaching and development
• Technical training and workshops
• Technical equipment for work (Mac / Windows)
• Company psychologist for mental well-being