Analytics Engineer

📋 Description

• End-to-end ownership of the Databricks env and project structure.
• Build internal tools (AI-assisted) to speed data investigation.
• Productionize tools into reliable automated solutions.
• Infrastructure & automation: Git workflows, GitLab deployments, ETLs/agents.
• Improve efficiency by automating repetitive manual work.
• Hands-on analytics: dive into data and balance building with analysis.

🎯 Requirements

• Python, PySpark, and advanced SQL proficiency.
• Solve vague problems and deliver working solutions independently.
• Solid software engineering fundamentals (Git, CI) and a mostly solo codebase.
• Good judgement on engineering effort; analytical correctness matters.
• Comfortable with AWS; or GCP/Azure with willingness to learn AWS.
• Quick to pick up new tools and work across multiple infrastructures.

🎁 Benefits

• Hybrid work model: 3 days in office, 2 days remote.
• Prague office in DOCK IN area with snacks, drinks, fruit, and Tue lunches.
• 5 weeks vacation, birthday day off, 3 sick days, Multisport.
• MacBook Pro M3, dual monitors, standing desks.
• Regular team-building, monthly birthday celebrations, baking Thursdays, happy hours.
• Equity and career growth opportunities.