Data Engineer

📋 Description

• Design, build, and maintain scalable data pipelines using Python, PySpark, and SQL.
• Develop, optimize, and maintain ETL and data transformation processes.
• Collaborate with Product/Design/Leadership/Engineering to translate requirements.
• Build scalable data models with SQL and clear documentation.
• Implement data quality checks and monitoring for accuracy and integrity.
• Optimize storage, retrieval, and processing for performance and cost.

🎯 Requirements

• 2–4 years in Data Engineering, in reporting-focused roles.
• Strong Python skills: dataframes, OOP, modular code.
• Practical PySpark and large-scale data processing experience.
• Strong SQL: complex queries, transformations, data quality checks.
• Data modeling and query optimization experience.
• Experience with scalable data infrastructure in SaaS/tech env.

🎁 Benefits

• Fully remote working environment across Europe.
• Competitive compensation and benefits.
• Healthcare-related tech sector exposure.
• Professional development opportunities.
• Tools and autonomy to perform effectively.
• Collaborative, international teams across countries.