Data Engineer - Analytics Platform (m/f/d)

Working place: Allschwil and Home- OfficeFor 26 years, Medgate has been bringing doctors directly to patients 24/7 thanks to telemedicine. At Medgate Switzerland, more than 300 motivated employees – including over 130 permanently employed doctors – are actively shaping the medicine of tomorrow with the help of future-oriented digital health solutions. Those who treat patients remotely at Medgate receive intensive training in telemedicine at the beginning. The medical guidelines developed for the needs of telemedicine and continuously refined over the years are practice-oriented and designed for remote treatment. The patient management system supports doctors in their treatment by using artificial intelligence, among other things. This means that doctors have less administrative work and can focus more specifically on their patients. The medicine of the future is already a reality at Medgate. With flexible working models and reliable duty scheduling, Medgate makes it easy to combine work, leisure and family life. About the roleAt Medgate, data plays a key role in shaping the future of healthcare. As a Data Engineer, you’ll design, build and operate our modern cloud data platform, enabling reliable insights for internal teams and customer-facing solutions. You’ll work with Azure Databricks, dbt and Power BI to transform data into valuable products while helping drive the evolution of our platform from a legacy Data Vault architecture to a modern dimensional (Kimball) model. Working closely with your team, you’ll combine technical excellence with AI-powered engineering practices to deliver scalable, high-quality data solutions. Your tasks Design, build and operate scalable data pipelines using Azure Data Factory and Databricks (batch and streaming). Develop and maintain robust dimensional data models (Kimball) using dbt within a modern bronze/silver/gold medallion architecture. Create and maintain semantic models, dashboards and reports in Power BI for internal stakeholders and external customers. Collaborate with business stakeholders to translate data requirements into reliable and scalable technical solutions. Own your data products end-to-end, ensuring high quality, documentation, monitoring and operational excellence. Contribute to infrastructure as code (Terraform), CI/CD processes and code reviews to continuously improve our platform. Ensure high standards of data quality, consistency and governance across all data products and pipelines, including the secure handling of sensitive data. Use AI tools such as Claude as an integral part of your daily engineering workflow to accelerate development, improve quality and solve complex data challenges. Your profile Must have Fluent English and French (spoken and written). German is a strong advantage. 5+ years of professional experience as a Data Engineer or in a comparable role. Hands-on experience with dbt and modern data transformation practices. Experience working with AI-powered development tools (e.g. Claude, ChatGPT or GitHub Copilot) to increase engineering productivity. Solid SQL skills and experience building reliable data pipelines. A degree in Computer Science, Data Science or a related field, or equivalent professional experience. Nice to have Experience with Azure Databricks and Azure Data Factory. Knowledge of dimensional data modelling (Kimball) and medallion architecture. Experience building semantic models, reports and DAX in Power BI. Familiarity with Infrastructure as Code (Terraform) and CI/CD pipelines. Experience with Unity Catalog or comparable data governance solutions. Python experience for data engineering or automation. Experience working with Data Vault environments. Experience deploying or supporting machine learning solutions in production. Experience in healthcare, insurance or other highly regulated industries. What we offer Work on meaningful projects that help shape the future of digital healthcare. Modern cloud-native technology stack including Azure Databricks, dbt, Power BI and AI-powered engineering tools. Hybrid working model with two office days per week (Tuesday and Wednesday) and flexible remote working on the remaining days. High level of ownership and the opportunity to actively shape our growing data platform. Collaborative, international working environment with short decision-making paths. Continuous learning opportunities and access to modern technologies.