Mid Data Engineer, RoomPriceGenie

• 2-4 years of professional Python experience, ideally in data engineering and/or backend systems
• Experience building and maintaining ETL/ELT pipelines in production environments, preferably on modern cloud data warehouses (e.g., Snowflake, Databricks, BigQuery, Redshift)
• Solid understanding of data modeling concepts, including analytics-ready schema design (fact/dimension modeling) and performance optimization
• Experience working with orchestrated data pipelines (e.g., Dagster, Airflow, or similar tools)
• Experience building backend or ingestion services using Python web frameworks such as Django, FastAPI, or Flask
• Familiarity with background task processing and asynchronous workflows (e.g., Celery or similar systems)
• Experience working with cloud infrastructure, preferably AWS (e.g., S3, RDS/Aurora)
• Understanding of software design principles and data pipeline architecture fundamentals
• Experience working with large datasets using tools such as pandas, polars, or NumPy
• Analytical mindset with an interest in data quality, KPIs, and data-driven decision-making
• Ownership mentality—you care about writing reliable, maintainable code and improving what you touch
• Familiarity with product-oriented data teams serving multiple stakeholders
• Fluent in English and comfortable participating in technical discussions
• Based within the European Time Zone (UTC+0 to UTC+2)

Desirable

• We're looking for product-minded Data Engineers who care as much about why we build something as how we build it
• At RoomPriceGenie, you'll work at the intersection of software engineering, data analytics, and business impact. You won't just build pipelines; you'll understand who relies on your work and what decisions it enables.
• Our data powers pricing recommendations for 3,000+ hotels worldwide, helping independent hoteliers set the right pricing. When you ship something here, you'll see the direct impact on real businesses and the people who run them
• Build and own. Design scalable data pipelines using our modern stack (Snowflake, Dagster, dbt) and take them from idea to production to monitoring. You'll own the full lifecycle
• Modernize with purpose. Help us migrate legacy Django/Celery pipelines to our modern platform. This is an opportunity to reshape how data flows through our entire product
• Bridge the gap. Work closely with Product, Analytics, and Engineering (Backend, Frontend, and Data Science). Translate business questions into technical designs. Ensure analysts and data scientists can actually use what you build
• Care about quality. Champion data reliability through testing, observability, and documentation. Multiple teams depend on your work daily; accuracy and trust are non-negotiable