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)
At a glance
Senior Data Analysis & BI role at Julius Baer. Zurich · full-time.
Pay not stated Data Engineer salary
dataroles summary, based on the employer's posting.
What you'll do
- Build and maintain data pipelines, products and backend services for live decisioning, reporting, analytics and AI
- Shape data models for analytical and operational use, keeping them fast, scalable and maintainable
- Write secure, testable code and create platform checks for data quality, governance and monitoring
- Work with cloud, security and architecture teams to align platform work with enterprise and cloud standards
What you bring
- A relevant technical degree or equivalent professional training and experience
- At least five years building enterprise data platforms, ETL or ELT pipelines, warehouses and data applications
- At least five years using Python, Scala or similar languages, plus SQL for analysis, tuning and troubleshooting
- Three or more years with cloud data technologies, and hands-on work with Databricks and Apache Spark
Who this fits
This senior role suits an experienced data engineer with strong platform, modelling and testing skills who works well in Agile teams. The position is in Zurich and is offered at an eighty to one hundred percent workload through an external payroll partner for twelve months, with a possible extension.
From the employer
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.YOUR CHALLENGE
- Design, develop, and maintain scalable data pipelines, data products, and backend services supporting real-time decisioning, reporting, analytics, and AI use cases
- Design and implement data models for analytical and operational workloads, ensuring performance, scalability, and maintainability.
- Produce high-quality, secure, testable, and maintainable code following engineering best practices
- Develop and maintain data governance, data quality, and monitoring solutions across the platform
- Collaborate with cloud, security, and architecture teams to ensure compliance with enterprise standards and cloud best practices
YOUR PROFILE
- 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 designing and implementing data engineering solutions and enterprise-scale data platforms
- 5+ years of experience building ETL/ELT pipelines, data warehouses, and modern data platform architectures
- 5+ years of experience developing and maintaining data applications and services using Python, Scala, or similar languages
- 5+ years of hands-on SQL experience, including performance optimisation, data analysis, and troubleshooting
- 3+ years of experience with cloud data technologies, preferably Databricks on Azure
- Strong hands-on experience building and optimising large-scale data processing solutions using Databricks and Apache Spark (PySpark, Spark SQL, Structured Streaming, Delta Lake)
- Experience working with structured, semi-structured, and unstructured data across a variety of data stores, including data warehouses, relational databases, object storage, and distributed data platforms.
- Solid understanding of data modelling principles
- Experience implementing CI/CD pipelines and automated deployment practices
- Strong design, implementation, and testing skills
- Excellent communication and collaboration skills, with experience working in Agile delivery environments
Additional or Preferred Qualifications:
- Strong experience with Infrastructure as Code using Terraform, including deployment, configuration, and management of Azure and Databricks resources
- Experience with event-driven architectures and streaming technologies, including Kafka, Azure Event Hubs, Event Grid, Apache Flink, or similar
- Experience with DBT and modern data transformation frameworks.
- Experience with Data Vault 2.0 modeling methodologies
- Ability to provide technical leadership and guide architectural and engineering decisions
We are looking forward to receiving your full job application through our online application tool. Further interesting job opportunities can be found on our Career site.
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