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; Vor Ort; CHF 140.000 - 180.000; Vollzeit

Zusammenfassung

Julius Baer in Zürich seeks a senior data platform engineer to design, develop, and maintain real-time data pipelines and backend services for decisioning, reporting, data collection, and related functions.

You will drive data governance and security, collaborating with analytics teams to deliver robust data platforms in a cloud-first environment. The role requires 5+ years in ETL/ELT, data warehousing, and cloud data tech, with Databricks, PySpark, Delta Lake, and Kubernetes/Docker experience.

Qualifikationen

• 5+ years of ETL/ELT, data warehousing, BI, and integrating data processing/workflow tools into pipeline design.
• 5+ years building and maintaining end-to-end data systems using Python, Scala, or similar programming languages.
• Bachelor’s or Master’s degree in Computer Science, Data Analytics, Information Systems, or related field; or equivalent training and professional experience.
• 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 CI/CD environments.
• Demonstrated experience with Databricks, PySpark, Spark Streaming, and Delta Lake.
• Hands-on experience with structured, semi-structured, and unstructured data across storage systems (RDBMS, data warehouses, caches, document databases).
• Familiarity with Azure Data Lake and Blob Storage; strong data modeling principles (Data Vault a plus).
• Experience with event-driven architectures (Kafka, Event Hubs, Apache Flink) and containerized microservices (Kubernetes, Docker).
• Knowledge of dbt and BI tools; excellent communication and collaboration, leadership capabilities.

Aufgaben

• 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 to improve data governance and security
• Develop processes to ensure Data Security and Data Quality

Kenntnisse

ETL/ELT

Data warehousing

Python

Scala

SQL

Azure

Databricks

PySpark

Spark Streaming

Delta Lake

RDBMS

Data modeling

CI/CD

Kubernetes

Docker

Azure Data Lake

dbt

BI tools

Ausbildung

Bachelor's degree in CS or related field

Master's degree in CS or related field

Equivalent experience

Tools

Databricks

PySpark

Spark Streaming

Delta Lake

Azure

Kubernetes

Docker

dbt

Azure Data Lake

Jobbeschreibung

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, ability to provide technical leadership to other developers