The Position
This role offers more than a position — it provides the opportunity to shape the future of data and analytics within Medicine. As a Senior Data Engineer Medicine & Analytics, you will be part of IT Enterprise Data & Platforms, AI & Platforms and will build and evolve reliable, scalable data products that enable high-impact insights, accelerate decision-making, and improve patient outcomes.
You will be a key contributor in delivering a modern data ecosystem across cloud and enterprise platforms. With a strong engineering mindset, you'll drive change, embrace continuous improvement, and thrive in a fast-moving environment where priorities evolve day by day.
Tasks & Responsibilities
- Design, build, and operate end-to-end data pipelines and integrations (batch and event driven), using SnapLogic and AWS services (S3, Lambda, Glue) to ensure scalable ingestion, transformation, and orchestration
- Develop performant analytics-ready data models and transformation layers, leveraging Snowflake and dbt for modeling, testing, documentation, and efficient deployment
- Ensure strong data governance, quality, and lifecycle management, working with Collibra for metadata/lineage and Attaccama for data quality rules, monitoring, and remediation, and supporting product lifecycle processes through Innovator
- Drive engineering excellence and operational reliability, applying best practices in version control, CI/CD, code reviews, observability, alerting, automation, and self-healing mechanisms
- Collaborate closely with cross functional partners (Product Owners, Data Scientists, Analysts, Architects, and business stakeholders) to translate needs into reliable, reusable, secure, and compliant data assets
Requirements
- Masters Degree in Computer Science, Engineering, Data/Information Systems, or a related field, with several years of relevant experience in data engineering, analytics engineering, or similar roles or a bachelors degree in these fields with more relevant experience
- Solid knowledge of software engineering fundamentals (Python/SQL, Git, coding standards, automated testing, and production support practices)
- Hands-on experience building integrations and pipelines using tools such as SnapLogic (or comparable iPaaS) and cloud services — specifically AWS S3, Lambda, and Glue as well as proven experience with dbt (models, tests, macros, documentation, environments, CI/CD integration) and strong experience with Snowflake including data modeling, performance tuning, and secure data access patterns
- Familiarity with data governance and metadata management, ideally with Collibra; understanding of lineage, stewardship, and data catalog practices
- Demonstrated ability to work independently, manage priorities, and proactively drive work forward in a dynamic environment as well as strong stakeholder management, analytical thinking, and structured problem-solving skills
- Excellent English (oral and written) and communication skills