Cloud Data Expert

ppWe are opening a bCloud Data Expert /b position to strengthen a team based in the canton of Vaud, Switzerland. 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. /p h3Job Responsibilities /h3 ul lipDevelop, review, troubleshoot and optimise production‑grade data solutions using Python and PySpark. /p /li lipMaintain Terraform modules and implement controlled enhancements to cloud data infrastructure. /p /li lipSupport and improve CI/CD pipelines, including testing, quality controls, release traceability and deployment reliability. /p /li lipConfigure and troubleshoot cloud and on‑premises connectivity, including virtual networks, firewalls, routing and DNS. /p /li lipContribute to the production support of a large‑scale data platform by investigating incidents, identifying root causes and improving operational resilience. /p /li lipWork directly with business stakeholders to clarify requirements and translate them into reliable, maintainable data solutions. /p /li lipCollaborate with data, integration, BI, infrastructure, architecture and security teams throughout the delivery lifecycle. /p /li lipProduce reusable technical documentation and support knowledge transfer through workshops, coaching, code reviews and practical training. /p /li /ul br/ ul lipIntermediate to advanced hands‑on expertise in Python and PySpark within production data environments. /p /li lipProven experience maintaining Terraform modules and implementing controlled infrastructure changes. /p /li lipSolid knowledge of CI/CD pipeline maintenance, troubleshooting and continuous improvement. /p /li lipExperience supporting a large, business‑critical enterprise data platform. /p /li lipStrong understanding of cloud and on‑premises networking, including virtual networks, firewalls and command‑line diagnostic tools. /p /li lipAbility to gather business requirements and convert them into clear technical designs and acceptance criteria. /p /li lipA structured approach to engineering quality, including testing, peer reviews, documentation, monitoring and operational readiness. /p /li lipExperience with dbt, Databricks, Kubernetes or Power BI, as well as team training and knowledge transfer, would be an advantage. /p /li /ul /p #J-18808-Ljbffr