Analytics Engineer
HybridPrague, Prague, Czechia
Job Summary
Own the Databricks development environment and project structure for the Data Enablement team, acting as the sole engineering role end-to-end. Build practical internal tools, including AI-assisted and automated solutions, to speed up data investigation and help customer-facing teams communicate insights. Productionize these tools by working directly with analysts to turn their analytical efforts into reliable automated solutions. Set up and maintain Git workflows, code reviews, and deployments in GitLab while managing automated ETLs and agents. Identify repetitive manual work across the team and automate it, balancing time between building infrastructure and diving directly into data analysis. Use AI coding assistants as a normal part of your workflow and collaborate with infrastructure teams to scale new solutions.
Required Qualifications
- Strong proficiency in Python, PySpark, and advanced SQL
- Solid grasp of software engineering fundamentals (Git, continuous integration, and the discipline to maintain a mostly one-person codebase)
- Ability to take a vague, messy problem and drive it to a working solution by planning, designing, and delivering independently
- Comfortable working with our AWS stack (or has a background in GCP/Azure with a genuine willingness to learn AWS)
- Ability to pick up new tools and build across a wide variety of infrastructures
- Ability to communicate clearly, particularly when translating technical concepts to non-engineers
- Ability to dig into why a number looks off before moving on
Desired Qualifications
- Experience or curiosity in building AI-powered applications
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