Senior Data Engineer – Cloud & Analytics; f​/m​/d our external payro

At Julius Baer, we celebrate and value the individual qualities you bring, enabling you to be impactful, to be entrepreneurial, to be empowered, and to create value beyond wealth. Let’s shape the future of wealth management together.

In our team, you will be a key contributor to building our Data Platform as a foundation for Data Analytics and AI.

• Design, develop, and maintain data pipelines and backend services for real-time decisioning, reporting, data collecting, and related functions
• Data Requirements and Modeling
• Data Management and Transformation
• Produce high-quality, well-tested, and secure code
• Develop and maintain software designed to improve data governance and security
• Develop processes designed to ensure Data Security and Data Quality

• Bachelor’s or Master’s degree in Computer Science, Data Analytics, Information Systems, or a related technical field; or equivalent training and professional experience
• 5+ years of experience in ETL/ELT, data warehousing, Business Intelligence, and integrating data processing/workflow management tools into pipeline design
• 5+ years building and maintaining end-to-end data systems using Python, Scala, or similar programming languages
• Solid experience in utilising SQL for data analysis, investigating data issues, diagnosing root causes, and designing effective solutions
• Experience in working with cloud-based data technologies, preferably on Microsoft Azure, within continuous integration and delivery (CI/CD) environments
• Demonstrated experience working with large-scale datasets using Databricks, PySpark, Spark Streaming, and Delta Lake
• Hands-on experience with structured, semi-structured, and unstructured data across various storage systems, including relational databases (RDBMS), data warehouses, in‑memory caches, and document databases
• Familiarity with cloud storage solutions such as Azure Data Lake and Blob Storage
• Solid understanding of data modelling principles (experience with Data Vault is a plus) and strong skills in system design, implementation, and testing
• Experience with event‑driven architectures (e.g., Kafka, Event Hubs, Apache Flink) and containerised microservices platforms (e.g., Kubernetes, Docker, Helm Charts)
• Knowledge and practical use of dbt (data build tool), experience with BI tools
• Excellent communication and collaboration skills, ability to provide technical leadership to other developers