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 teams to translate requirements into
• Build scalable data models with SQL and provide clear documentation.
• Implement data quality checks, monitoring, and validation to ensure data accuracy and integrity.
• Optimize storage and retrieval for performance, scalability, and cost efficiency.

🎯 Requirements

• 2–4 years in a Data Engineering role, preferably with internal, financial, or operational reporting.
• Strong Python proficiency (dataframes, OOP, modularity, maintainable code).
• Practical experience with PySpark and large-scale data processing.
• Strong SQL skills with complex queries, transformations, and data quality checks.
• Experience with data modeling and query optimization.
• Experience building or maintaining scalable data infrastructure in a SaaS/tech environment is

🎁 Benefits

• Fully remote working environment across Europe.
• Competitive compensation and benefits.
• Opportunity to work in healthcare-related technology sector.
• Meaningful impact on products supporting professionals and digital patient care.
• Learning and professional development opportunities.
• Access to tools and technologies to perform effectively.