Data Engineer

📋 Description

• Design, build, and maintain scalable data pipelines using Python, PySpark, and SQL.
• Develop, optimize, and maintain ETL and data transformation processes for internal reporting and
• Collaborate with product, design, leadership, and engineering to translate requirements into data
• Build scalable data models with SQL and comprehensive documentation.
• Implement data quality checks, monitoring, and validation to ensure data accuracy and integrity.
• Optimize data storage, retrieval, and processing for performance and cost efficiency.

🎯 Requirements

• 2–4 years of professional Data Engineering experience.
• Strong Python proficiency (dataframes, OOP, modularity, maintainable code).
• Practical experience with PySpark and large-scale data processing.
• Strong SQL skills for complex queries, transformations, and data quality checks.
• Experience with data modeling and query optimization.
• Experience with scalable data infrastructure in SaaS/tech environment preferred.

🎁 Benefits

• Fully remote working environment across Europe.
• Competitive compensation and benefits.
• Opportunity to work in healthcare-related technology sector.
• Ownership within an evolving engineering environment.
• Professional development opportunities and access to modern tools/tech.
• Collaborative, international team across multiple countries.