About the Role
Grape Up is a consulting & technology company helping enterprises create the most important applications by leveraging AI & cloud-native technologies and modern ways of delivering software. Our projects are based on cooperation with international clients from government and industries such as automotive, insurance and finance.In cooperation with our client, we are building and operating an on-prem data platform used for large-scale engineering and R&D data processing. Our role focuses on Kubernetes-based infrastructure, automation, and close collaboration with data engineering teams to ensure scalability and reliability.We are building a talent pool for upcoming opportunities. If your skills and experience match the criteria listed, you are welcome to apply. We will contact candidates who best fit new projects as soon as relevant positions opeResponsibilitiesMaintain, operate, and continuously improve a Kubernetes-based, on-prem data platform supporting data engineering and analytics workloadsDevelop and maintain CI/CD pipelines and deployment processes using ArgoCD and GitHub ActionsEnsure high platform reliability, scalability, and observability through proper monitoring and logging solutionsAutomate infrastructure and platform operations using Python, including scripts, Kubernetes operators, and DAGsCollaborate closely with data engineers and platform users to support and improve data processing environmentsRequirementsStrong hands-on experience with Kubernetes in production environmentsExperience with CI/CD pipelines and deployment automation (ArgoCD, Github Actions or similar tools)Solid knowledge of monitoring and logging in distributed systems (Prometheus, Grafana, Elasticsearch or equivalents)Proficiency in at least one programming language – preferably PythonGood communication skills, both written and spokenGood command of English (B2 /C1)Nice to haveFamiliarity with data processing and analytics tools such as Spark, Airflow, Jupyter, or Apache IcebergExperience supporting data engineering or data science platformsPrevious exposure to large, on-premises infrastructures and open-source–based ecosystems