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Posted 2h agoNyon, Vaud, Suisse

Cloud Data Expert

SeniorOn-site (Nyon)Salary undisclosed
Required Skills
PythonKubernetesTerraformCI/CDDatabricks
Job Description

We are opening a Cloud Data Expert position to strengthen a team based in Nyon & Lausanne. The role will contribute to the development and operational reliability of an enterprise Cloud Data Platform, combining hands-on data engineering, cloud infrastructure, DevOps and hybrid networking expertise.

Job Responsibilities

  • Develop, review, troubleshoot and optimise production-grade data solutions using Python and PySpark.

  • Maintain Terraform modules and implement controlled enhancements to cloud data infrastructure.

  • Support and improve CI/CD pipelines, including testing, quality controls, release traceability and deployment reliability.

  • Configure and troubleshoot cloud and on-premises connectivity, including virtual networks, firewalls, routing and DNS.

  • Contribute to the production support of a large-scale data platform by investigating incidents, identifying root causes and improving operational resilience.

  • Work directly with business stakeholders to clarify requirements and translate them into reliable, maintainable data solutions.

  • Collaborate with data, integration, BI, infrastructure, architecture and security teams throughout the delivery lifecycle.

  • Produce reusable technical documentation and support knowledge transfer through workshops, coaching, code reviews and practical training.

  • Intermediate to advanced hands-on expertise in Python and PySpark within production data environments.

  • Proven experience maintaining Terraform modules and implementing controlled infrastructure changes.

  • Solid knowledge of CI/CD pipeline maintenance, troubleshooting and continuous improvement.

  • Experience supporting a large, business-critical enterprise data platform.

  • Strong understanding of cloud and on-premises networking, including virtual networks, firewalls and command-line diagnostic tools.

  • Ability to gather business requirements and convert them into clear technical designs and acceptance criteria.

  • A structured approach to engineering quality, including testing, peer reviews, documentation, monitoring and operational readiness.

  • Experience with dbt, Databricks, Kubernetes or Power BI, as well as team training and knowledge transfer, would be an advantage.

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