Senior Data Manager

About the role

The Senior Data Manager is responsible for owning key data topics across products, including dataset creation, data export, annotation workflows, and performance monitoring, and for driving those topics end‑to‑end. This role makes structuring decisions on team tooling and data architecture, builds reusable pipelines and automation, and mentors more junior data team members. Work is done with radiologists, product managers, AI engineers, clinical research scientists, and data engineers to support medical product development.

Key responsibilities

• Own one or several data topics across products, such as dataset creation, data export, annotation workflows, and performance monitoring, and drive them end‑to‑end.
• Design and maintain reusable tooling, including pipelines, dashboards, and automation, for the data team and stakeholders.
• Make structuring decisions on technical implementation, team tooling, and data architecture, ensuring code quality and process efficiency.
• Surface actionable insights from the data lake and deliver relevant information to product, AI, and clinical stakeholders.
• Establish annotation guidelines and training to maintain consistent annotation quality.
• Mentor junior data team members through technical guidance and knowledge sharing.

Required profile

• Master’s degree in a health‑related or scientific field.
• 5+ years of experience in data management, data engineering, or data science, preferably in healthcare or medical imaging.
• Strong analytical and scientific mindset with excellent attention to detail.
• Ability to manage multiple topics in parallel while keeping a broader view of product and data priorities.
• Effective communication skills to translate needs between technical and non‑technical stakeholders.

Required skills

• Python programming.
• Database query languages (SQL) and experience with BigQuery and MongoDB.
• Automated testing and code versioning (e.g., Git) with review processes.
• Knowledge of medical imaging and its role in AI algorithm development.
• Experience building reusable data pipelines and automation.