In this role, you will shape the data foundations behind AI-driven products and workflows. As a Senior Data Engineer | Data Ops, you will connect complex data sources, strengthen the reliability of critical systems, and partner with Product, Engineering, and Data Science to support high-impact work across the business.

What you will do: - Design and maintain high-performance, secure, and scalable data pipelines to support AI-driven workflows. - Drive data integration: collaborate with cross-functional teams to autonomously manage the ingestion, transformation, and integration of large datasets from external partners. - Enhance data quality and compliance: build systems to ensure data quality, integrity, and regulatory compliance (ISO 13485, GDPR). - Build and automate: develop reusable code and frameworks to streamline data processes and ensure operational excellence. - Monitor and troubleshoot: monitor data pipelines, resolve issues autonomously, and implement safeguards to minimize disruptions. - Innovate: identify and implement best practices and emerging technologies to enhance data infrastructure and team efficiency. - Collaborate globally: serve as a technical expert, working closely with Product, Engineering, and Data Science teams to ensure align

In this role, you will shape the data foundations behind AI-driven products and workflows. As a Senior Data Engineer | Data Ops, you will connect complex data sources, strengthen the reliability of critical systems, and partner with Product, Engineering, and Data Science to support high-impact work across the business.

What you will do: - Design and maintain high-performance, secure, and scalable data pipelines to support AI-driven workflows. - Drive data integration: collaborate with cross-functional teams to autonomously manage the ingestion, transformation, and integration of large datasets from external partners. - Enhance data quality and compliance: build systems to ensure data quality, integrity, and regulatory compliance (ISO 13485, GDPR). - Build and automate: develop reusable code and frameworks to streamline data processes and ensure operational excellence. - Monitor and troubleshoot: monitor data pipelines, resolve issues autonomously, and implement safeguards to minimize disruptions. - Innovate: identify and implement best practices and emerging technologies to enhance data infrastructure and team efficiency. - Collaborate globally: serve as a technical expert, working closely with Product, Engineering, and Data Science teams to ensure align