Data Operations Engineer 100% (f/m/d)
Bank Julius Bär & Co. AG
Publication date:
10 October 2024Workload:
100%- Place of work:Zürich
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.
As data platform data engineer you manage daily data operations based on data lake on-prem environment. You closely collaborate with the development team and taking care of the platform data related issues.
IHRE AUFGABEN
- Datasets and data pipelines preparation, support for Business, data troubleshooting.
- Closely collaborate with the Program Management and stakeholders
- Develop data pipelines and structures for Data Analysts, testing such to ensure that they are fit for use
- Maintain and model JSON based schemas and metadata to re-use it across the organization (with central tools)
- Resolving and troubleshooting data related issues and queries
- Covering all processes from enterprise reporting to data science (incl. ML Ops)
YOUR PROFILE
Competencies:
- Hands-on Big Data experience using common components (Hive, Spark, Presto/Trino, NiFi, MinIO, K8S, Kafka, S3 Storage)
- Experience in stakeholder management in heterogeneous business/technology organizations
- Experience in banking or financial business, with handling sensitive data across regions
- Experience in large data migration projects with on-prem Data Lakes a plus
- Hands-on experience in Data Science Workbench platforms (e.g. Knime, Cloudera, Dataiku)
- Track record in Agile project management and methods (e.g., Scrum, SAFe)
Education and skills requirements
- Knowledge of reference architectures, especially concerning integrated, data-driven landscapes and solutions
- Expert SQL skills, preferably in mixed environments (i.e. classic DWH and distributed)
- Working automation and troubleshooting experience in Python using Jupyter Notebooks or common IDEs
- Data preparation for reporting/analytics and visualization tools (e.g Tableau, Power BI or Python based)
- Applying a data quality framework within the architecture
- Good knowledge of German is beneficial, excellent command of English is essential
- Higher education (e.g. “Fachhochschule”,“Wirtschaftsinformatik”)
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