Data Engineer

📋 Description

• Design, build, and maintain scalable data pipelines using Python, PySpark, and SQL.
• Develop, optimize ETL and data transformation processes for internal reporting and products.
• Collaborate with Product, Designers, Leadership, and Engineering to translate requirements into
• Build scalable data models with SQL and document them clearly.
• Implement data quality checks and monitoring to ensure data accuracy and integrity.
• Optimize storage and retrieval for performance, scalability, and cost.

🎯 Requirements

• 2–4 years in a Data Engineering role, with internal/financial/operational reporting experience.
• Strong Python proficiency (dataframes, OOP, modular code).
• Experience with PySpark and large-scale data processing.
• Strong SQL skills with complex queries and data quality checks.
• Data modeling and query optimization experience.
• Experience with scalable data infrastructure in SaaS/tech environments; Databricks and dbt are a

🎁 Benefits

• Fully remote across Europe.
• Competitive compensation and benefits.
• Meaningful healthcare-related tech work and impact on patient care.
• Professional development opportunities.
• Access to modern tools and technologies.
• Autonomy within an evolving engineering environment.