Design, build, and maintain scalable and reliable data pipelines using Python, PySpark, and SQL
Develop and optimize data transformations and ETL processes, ensuring data accuracy and relevance for our clients
Collaborate with Product Managers and Designers to understand data requirements and deliver effective solutions that meet client needs
Build scalable and discoverable data models in SQL and maintain detailed documentation for each
Implement data quality checks and monitoring to ensure data accuracy and integrity
Optimize data storage and retrieval for performance and cost efficiency
Contribute to cluster optimization and maintenance
Document data engineering processes and best practices

At least 2-4 years of experience in a Data Engineering role
Proficiency in Python (core + dataframes)
Focus on Object-Oriented Programming and modularity
Experience with PySpark for large-scale data processing
Solid SQL skills, including the ability to write complex queries and quality checks
Proven experience in data modeling and query optimization
Experience with Databricks is a big plus, experience with DBT is required
Experience with databases like ClickHouse is a big plus
Experience with data visualization tools (e.g., Tableau, PowerBI, Looker) is a plus
Knowledge of DevOps principles, CI/CD practices and security is an advantage
Full proficiency in English, written and spoken.

The chance to work in a meaningful industry and in a fast-growing, global company on a path to changing digital healthcare
Competitive compensation and benefits
Learning and professional growth opportunities
The tools you need, and enjoy using
Frequent company events and talented colleagues from around the world

Data Engineer

Key skills