Requirements

Expected technologies

SQL

ClickHouse

Python

Docker

Git

Optional technologies

Hugging Face

scikit-learn

R

Our requirements

• 2–5 years of commercial experience in data engineering, with at least 2 years focused on ETL and pipelines
• Proficiency in SQL and ClickHouse, with solid understanding of AI-informed data processing
• Hands-on experience with Python (pandas, NumPy), Docker, and Git
• Interest or experience in Web3 technologies is highly welcome
• Strong focus on scalable system design and data architecture quality
• Proactive, independent, startup-minded collaborator
• English at B2 technical level; fluent Polish is a bonus

Optional

• Familiarity with APIs, open-source ecosystems, Hugging Face, scikit-learn, and R is a plus

Your responsibilities

• Build and maintain ETL pipelines and scalable data infrastructure using SQL and ClickHouse
• Contribute to AI-driven data workflows and architecture
• Develop data-processing logic using Python and libraries like pandas and NumPy (when needed)
• Leverage Docker to manage development environments
• Collaborate using Git for version control, branching strategy, and team workflows
• Design clean, modular code, manage dependencies, write unit/integration tests, and maintain API documentation
• Support open-source contributions and integrate AI/ML tools like Hugging Face or scikit-learn where applicable
• Ensure high-quality, scalable data architecture suitable for real-time systems
• Communicate clearly in English (B2) and Polish (fluent preferred)
• Thrive in a proactive, independent role within a vibrant startup culture