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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 -
Zürich, ZH

Soumettre votre candidature

Détails de l'emploi

Temps de travail : 90-100%

Qualifications

CI/CD
Gestion du personnel
Spark
Analyse de données
Conception de systèmes
Niveau Master
Bases de données
SQL
Docker
Niveau Licence
Leadership
Compétences en communication
Python

Description complète du poste

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 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

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 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, a bility to provide technical leadership to other developers

We are looking forward to receiving your full job application through our online application tool.

Soumettre votre candidature

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