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)
Julius Baer is hiring a 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) in Zurich, Switzerland. Level rates it ; you can apply on Julius Baer.
Level's read on this job
- On Level's scale, this data engineer role is Works on AI ●●●○: the daily work is on AI products, without building the model.
- Tools and skills the posting cites include Databricks.
- Level classifies it as a senior role.
- Level lists 191 other open roles at Julius Baer.
AI in this role
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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How we rate this
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 Julius Baer rates 66 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.
Works on AI. The daily work is on AI products, without building the model.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Also common in data engineer jobs at this level
Pay
- Typical data engineer job
- $150k
This posting doesn't list pay. Use the typical data engineer figure when pay comes up. See data engineer jobs
Questions you could be asked
- What's a project where you used Databricks hands-on?
- Describe a typical day in a role like this one: which parts run through AI directly?
- If you removed AI from this role, what would be left, and how do you decide what still needs a human?
Adapt your resume
- List these exact terms on your resume: Databricks. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.
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