Data DevOps Engineer

Wymagania: - Systems & Scripting: Strong proficiency in Linux/Unix administration and Shell scripting.- Programming: Advanced knowledge of Python and SQL.- Mindset: Exceptional analytical and problem-solving skills.- Education: Degree in Computer Science, Data Engineering, or a related technical field.- Experience: 3–5 years of proven experience in Data Engineering or a DevOps-related role.Nice-to-have - Cloud & Big Data: Hands-on experience with Azure, Apache Spark, and Databricks.- DevOps Tools: Proficiency with Docker, Kubernetes, CI/CD tools, and IaC (e.g., Terraform, Ansible).- Data Ecosystems: Familiarity with Big Data technologies such as Hadoop or Kafka. Codzienne zadania: - Infrastructure Management: Build and maintain scalable data platforms and cloud-based infrastructure. - Automation: Implement CI/CD pipelines for data workflows and automate manual processes using Infrastructure as Code (IaC). - Pipeline Optimization: Monitor, troubleshoot, and optimize data processing jobs to ensure high availability. - Security & Compliance: Ensure data integrity and security across all environments. - Collaboration: Work closely with Data Scientists and Engineers to streamline the deployment of data models.