Your Role
- Design, Build, and Maintain Data Pipelines: Develop and maintain scalable, reliable, and efficient ETL (Extract, Transform, Load) pipelines using Azure tools and Databricks to handle large datasets from medical devices in the field.
- Data Integration: Integrate data from various sources (e.g., medical devices, regulatory systems, clinical databases) into centralized data lakes or data warehouses using Azure Data Factory, Databricks, and other relevant tools.
- Collaborate and work with Cross-Functional Teams: Work closely with clinical, regulatory, and quality assurance teams to ensure that data collected meets regulatory requirements (e.g., FDA, ISO 13485, MDR) and supports post-market surveillance activities.
- Data Security and Compliance: Ensure all data systems comply with industry regulations and data privacy standards.
- Continuous Improvement: Stay up-to-date with the latest advancements in data engineering, cloud technologies (specifically Azure), and medical device industry trends, and proactively suggest improvements to existing systems.
You're the Right Fit If You Have:
- A Master’s degree in Computer Science, Data Science, or a related field.
- A Minimum of 6-7 years of experience as a Data Engineer or in a related role, with a focus on data integration, ETL processes, and database management.
- Strong proficiency in Python and SQL, with hands-on experience in writing complex SQL queries and Python scripts for data processing.- MANDATORY
- Experience with Azure cloud services, including Azure Data Factory, Azure SQL Database, Azure Data lake and Databricks.