Data DevOps Engineer

Key Responsibilities

• 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.

Requirements

• 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.