Databricks Data Platform Engineer for Scalable Pipelines

Cleeven group; Basel; On-site; CHF 120,000 - 180,000; Full time

Job summary

CLEEVEN is seeking a Databricks Data Platform Engineer to support the industrialization, scalability and reliability of a Databricks-based data platform within a fast-growing industrial company.

You will work closely with data, cloud, integration and architecture teams to structure the platform, design scalable data pipelines and implement lakehouse patterns using Spark, PySpark and SQL on Azure. Fluency in English is required for collaboration across the organization.

Qualifications

• Strong hands-on experience with Databricks and data engineering on cloud platforms.
• Proficient in Spark, PySpark, SQL and Delta Lake concepts.
• Understanding of lakehouse architecture, data governance and security principles.
• Fluent English required, strong communication in a global team.

Responsibilities

• Contribute to the industrialization of the Databricks platform.
• Design, develop and optimize scalable data pipelines.
• Implement robust data engineering patterns using Spark, PySpark and SQL.
• Support the structuring of a lakehouse architecture based on Databricks.
• Improve performance, reliability, monitoring and maintainability of data workflows.
• Contribute to data quality, access management and platform governance topics.
• Collaborate with integration teams on data ingestion.
• Support deployment practices, documentation and platform standards.
• Transform business and technical requirements into scalable data solutions.

Skills

Databricks

Spark

PySpark

SQL

Delta Lake

Lakehouse

Azure

CI/CD

Git

DevOps

Data governance

Data quality

Security

English

Job description

CLEEVEN is seeking a Databricks Data Platform Engineer to support the industrialization, scalability and reliability of a Databricks-based data platform within a fast-growing industrial company.

You will work closely with data, cloud, integration and architecture teams to structure the platform, design scalable data pipelines and implement lakehouse patterns using Spark, PySpark and SQL on Azure. Fluency in English is required for collaboration across the organization.