DevOps Engineer

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 ope

Responsibilities

• Maintain, operate, and continuously improve a Kubernetes-based, on-prem data platform supporting data engineering and analytics workloads

• Develop and maintain CI/CD pipelines and deployment processes using ArgoCD and GitHub Actions

• Ensure high platform reliability, scalability, and observability through proper monitoring and logging solutions

• Automate infrastructure and platform operations using Python, including scripts, Kubernetes operators, and DAGs

• Collaborate closely with data engineers and platform users to support and improve data processing environments

Requirements

• Strong hands-on experience with Kubernetes in production environments

• Experience 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 Python

• Good communication skills, both written and spoken

• Good command of English (B2+/C1)

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Nice to have

• Familiarity with data processing and analytics tools such as Spark, Airflow, Jupyter, or Apache Iceberg

• Experience supporting data engineering or data science platforms

• Previous exposure to large, on-premises infrastructures and open-source–based ecosystems