Lead Data Engineer (Data Platform Owner)

Quick Facts

Lead Data Engineer (Data Platform Owner) responsible for the direction and build-out of a production data platform.

Description

You will own the data platform end-to-end—set its direction, decide on architecture and tools, and build solutions yourself with a small team. The platform powers daily internal applications; you’ll evolve integrations, orchestration, transformations, internal web apps, and the semantic/AI layer for querying data. You will also work closely with Finance, Revenue Management, Operations, and leadership to find and validate opportunities to reduce costs and increase revenue.

Responsibilities

• Own the data platform and define its roadmap.
• Make decisions on architecture, tooling, what to build next, and what to stop.
• Lead a teammate with clear goals while both code and conduct reviews (you set direction, but don’t split into manager vs builder).
• Identify where data can generate savings or increase revenue; propose improvements using business metrics.
• Build and extend internal applications on the company’s shared framework.
• Keep the platform running: connect sources, manage Airflow pipelines, model data in Snowflake, debug stale or inconsistent data.
• Develop the semantic layer and Avalanche (internal AI chat tool over Snowflake), including metric definitions and metadata.

Requirements

• Strong opinion on how to build and evolve a data platform; able to defend and update your decisions based on better arguments.
• Experience leading while still actively coding; ability to drive a small teammate forward without simply delegating tasks.
• Strong SQL and data modeling skills, including understanding data relationships, duplicates, and data validation.
• Production experience with data warehouses, transformations, and orchestration.
• Comfort with Snowflake, dbt, and Airflow (or comparable tooling).
• Strong coding capability; ability to take work from idea to production and ensure it works after deployment.
• Experience with Git and using AI as a normal part of development.
• Interest in business outcomes; ability to speak with Finance/Revenue/Operations and understand hotel performance drivers.

Benefits

• Direct impact on revenue and costs.
• Hybrid work; office in central Prague (Staroměstská).