Senior Data Engineer

• 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 for stakeholders who need to access, explore, or use the data.
• Make structuring decisions on technical implementation, team tooling, and data architecture, and maintain codebase quality and process efficiency.
• Surface actionable insights from the data lake by identifying, structuring, and delivering relevant information to product, AI, and clinical stakeholders.
• Drive the targeting and collection of relevant data.
• Build and structure medically consistent and representative datasets.
• Establish annotation guidelines and training so annotation quality stays consistent.
• Contribute to ongoing oversight and refinement of AI algorithm performance.
• Mentor more junior data team members through technical guidance and knowledge sharing.
• Write automated tests and apply code versioning and review standards to data processes and tools.

• Master’s degree in a health-related or scientific field (required).
• 5+ years of relevant experience in data management, data engineering, or data science, ideally in healthcare or medical imaging (required).
• Excellent proficiency in Python and database query languages, and comfort working with databases such as BigQuery and MongoDB (required).
• Ability to structure, document, industrialize, and optimize data processes and tools (required).
• Experience writing automated tests and working with code versioning and review (required).
• Knowledge of medical imaging and of how data and annotations shape AI algorithm development (required).
• Strong reasoning, attention to detail, and an analytical and scientific mindset (required).
• Ability to translate needs between technical and less technical stakeholders and to mentor others (required).
• Ability to manage multiple topics in parallel while maintaining a broader view of product and data priorities (required).
• Preferred: Machine learning understanding.
• Preferred: Experience with medical device development

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Quality Standards

• Communicates, cooperates, and consistently functions professionally and harmoniously with all levels of supervision, co-workers, visitors, and vendors.
• Demonstrates initiative, personal awareness, professionalism and integrity, and exercises confidentiality in all areas of performance.
• Follows all local, regional and country laws concerning employment.
• Follows all DeepHealth policies and procedures.
• Follows data privacy, compliance, safety and confidentiality standards at all times.
• Practices universal safety precautions.
• Promotes good public relations on the phone and in person.
• Adapts and is willing to learn new tasks, methods, and systems.
• Reports to work regularly as scheduled; consistently punctual with respect to working hours, meal and rest breaks, and maintains satisfactory personal attendance in accordance with DeepHealth guidelines.
• Completes job responsibilities in a quality and timely manner., The employee must be able to perform the essential duties and responsibilities of the position, with or without reasonable accommodation.