Data Engineer

Summary

Join Owkin as a Data Engineer and contribute to the development and maintenance of data pipelines for scientific processing and quality assurance. You will be responsible for designing, optimizing, and maintaining ETL/ELT pipelines using Airflow, ensuring reliability, scalability, and compliance with data governance standards. Your role will involve organizing and structuring data systems, ensuring accurate reporting of pipeline performance, and contributing to scientific and healthcare data processing workflows. You will work closely with engineers, data scientists, and researchers to deliver high-quality data solutions, focusing on streamlining production workflows, ensuring proper monitoring and operational efficiency, and implementing best practices for data governance and security.

Requirements

• Proficiency in Python and SQL
• Familiarity with Airflow for workflow orchestration
• Familiarity with cloud-based data storage and cloud-native processing concepts
• Familiarity with containerization technologies such as Docker and Kubernetes
• Knowledge of data governance and security fundamentals
• Ability to work with structured and unstructured datasets in predefined formats

Responsibilities

• Support the design and optimization of data pipelines using Airflow
• Develop and operate Python and SQL-based solutions for data processing
• Contribute to the development of scalable ETL/ELT pipelines to process and transform datasets
• Work closely with data scientists, business developers, software engineers, and biomedical researchers to deliver high-quality data solutions
• Contribute to management and monitoring of containerized data infrastructures with Docker, Kubernetes, and cloud platforms
• Follow best practices for data governance, security, and compliance in all workflows
• Operate on the data architectures, including data lakes, data warehouses, and analytical insights platforms
• Contribute to the productionization of data processing pipelines, ensuring efficiency and scalability in scientific data workflows

Benefits

• Flexible work organization
• Friendly and informal working environment
• Opportunity to work with an international team with high technical and scientific backgrounds