Ingénieur de données/Ingénieure de données

CLEEVEN; Basel; Vor Ort; CHF 90.000 - 120.000; Vollzeit

Zusammenfassung

CLEEVEN, a consulting company in Switzerland, is seeking a Databricks Data Platform Engineer to enhance the industrialization and scalability of its data platform. This role involves designing robust data pipelines, collaborating with multiple teams, and contributing to the platform's optimization for production readiness.

The ideal candidate will have strong experience with Databricks, Spark, and cloud environments. Proficiency in data governance and performance optimization are highly valued.

Qualifikationen

• Strong hands-on experience with Databricks.
• Solid experience in data engineering and cloud-based data platforms.
• Good knowledge of Spark, PySpark and SQL.
• Experience with Delta Lake or lakehouse architecture.

Aufgaben

• Contribute to the industrialization of the Databricks platform.
• Design, develop and optimize scalable data pipelines.
• Support deployment practices, documentation and platform standards.

Kenntnisse

Databricks

Spark

PySpark

SQL

Data Engineering

Cloud Environments

CI/CD

DevOps Practices

Data Governance

Jobbeschreibung

CLEEVEN is a European consulting company built around two core convictions:

• The excellence of European engineers should be a driver of global competitiveness
• Our human mission: supporting our consultants in their personal and professional development

As part of the scale-up of a modern data platform for a fast-growing industrial company, we are looking for a Databricks Data Platform Engineer to support the industrialization, scalability and reliability of a Databricks-based environment.

Context

The company is strengthening its data capabilities to support business, manufacturing, analytics and digital transformation initiatives.

The current objective is to move from a developing data platform to a more industrialized, scalable and production-ready environment. Databricks is at the center of this data ecosystem and is connected to multiple applications and data sources.

The consultant will work closely with data, cloud, integration, application and architecture teams to structure the platform and support upcoming projects.

Objectives

• 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 working on application connectivity and data ingestion
• Support deployment practices, documentation and platform standards
• Help transform business and technical requirements into scalable data solutions
• Strong hands-on experience with Databricks
• Solid experience in data engineering and cloud-based data platforms
• Good knowledge of Spark, PySpark and SQL
• Experience with Delta Lake, lakehouse architecture or modern data platforms
• Understanding of data pipeline industrialization, scalability and performance optimization
• Experience with cloud environments, ideally Microsoft Azure
• Knowledge of CI/CD, Git, DevOps practices or Infrastructure as Code would be an asset
• Good understanding of data governance, data quality and security principles
• Fluent English is required

Profile

We are looking for a technical and pragmatic profile, able to develop, structure and scale a Databricks environment in a complex enterprise context.

You are comfortable working on both implementation and platform improvement topics. You understand that the challenge is not only to build data pipelines, but also to make them reliable, maintainable and ready for long-term use.

Experience in industrial, manufacturing, pharmaceutical or regulated environments would be a strong advantage, but is not mandatory.