Senior Data Engineer – Data Analytics Platform 80-100% (f/m/d) - (Contract through our external payroll partner with immediate start for 12 months with possible extension)

The Senior Data Engineer, Data Analytics Platform will join Julius Baer, the leading Swiss wealth‑management group, to help build the core Data Platform that underpins analytics and AI initiatives across the firm. In this position you will design, develop and keep operational the data pipelines and backend services that feed real‑time decision making, reporting and data‑collection processes. Your work will involve modelling data requirements, transforming and managing data flows, writing well‑tested and secure code, and creating tools that strengthen data governance, security and quality. The role requires a university degree (Bachelor's or Master's) in Computer Science, Data Analytics, Information Systems or a comparable field, or equivalent professional training. You must bring at least five years of experience in ETL/ELT, data‑warehousing and Business‑Intelligence pipeline design, as well as five years of hands‑on work building end‑to‑end data systems with Python or Scala. Strong SQL skills for analysis and problem solving, proven use of cloud data services, preferably Microsoft Azure, in CI/CD pipelines, and extensive experience handling large‑scale datasets with Databricks, PySpark, Spark Streaming and Delta Lake are essential. You should also be comfortable working with structured, semi‑structured and unstructured data across relational databases, data warehouses, in‑memory caches and document stores, and possess excellent communication and leadership abilities to guide fellow developers. Additional assets include knowledge of Data Vault modelling, familiarity with event‑driven architectures such as Kafka or Event Hubs, experience with container platforms like Kubernetes and Docker, and practical use of dbt and BI tools. Julius Baer operates from Zurich and maintains a presence in about 60 global locations, offering an international, collaborative environment and flat hierarchies that support rapid growth and continuous learning. What the role asks for: - Bachelor's or Master's degree in CS, Data Analytics, IS or equivalent - 5+ years ETL/ELT, data‑warehousing, BI pipeline experience - 5+ years building data systems with Python or Scala - Strong SQL expertise for analysis and troubleshooting - Cloud data experience, preferably Microsoft Azure, in CI/CD - Large‑scale dataset work with Databricks, PySpark, Spark Streaming, Delta Lake - Hands‑on with structured, semi‑structured, unstructured data across RDBMS, warehouses, caches, document DBs - Excellent communication and technical leadership skills