Senior Data Engineer - Databricks | PySpark | Spark Streaming

Experis Switzerland; Zürich; On-site; CHF 110,000 - 165,000; Full time

Job summary

Experis Switzerland is hiring for a data engineering role in Zurich to design and maintain data pipelines and backend services for real‑time decisioning, reporting, and governance. You will define data models, manage data across the platform, and ensure secure, well-tested code.

The ideal candidate has 5+ years in ETL/ELT, data warehousing, and building end‑to‑end data systems with Python/Scala, plus strong SQL and cloud experience (Azure).

Qualifications

• 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 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, 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 (Data Vault a plus) and strong skills in system design, implementation, and testing.
• Experience with event‑driven architectures (Kafka, Event Hubs, Apache Flink) and containerised microservices platforms (Kubernetes, Docker, Helm Charts).
• Knowledge of dbt and BI tools.

Responsibilities

• Design, develop, and maintain data pipelines and backend services for real-time decisioning, reporting, data collecting, and related functions.
• Define data requirements and develop data models.
• Manage and transform data across the platform.
• 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.

Skills

ETL/ELT

Data warehousing

Python/Scala

SQL

Azure Cloud

CI/CD

Databricks

PySpark

Kubernetes

Docker

Data modelling

Data Vault (plus)

Data governance

Kafka/Event Hubs

Education

Bachelor's or Master’s in CS/Data Analytics/IS

Tools

dbt

Azure Data Lake

Delta Lake

Spark

Kafka

Kubernetes

Docker

Databricks

Job description

Location: Zurich

Start date: ASAP

Duration: 12months – with possibility of extension

Key Responsibilities

• Design, develop, and maintain data pipelines and backend services for real-time decisioning, reporting, data collecting, and related functions
• Define data requirements and develop data models
• Manage and transform data across the platform
• 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

Qualifications

• 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

Due to Swiss work permit restrictions, we can only consider applications from EU citizens or holders of valid working permit in Switzerland.

Experis is a global leader in IT professional resourcing, permanent recruitment, project solutions, and managed services. With over 25 years of experience in Switzerland and offices in Zürich, Basel, and Geneva, we connect top IT talent with leading companies. Our mission is to help professionals unlock their potential and thrive in dynamic, future-ready careers.