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Azure Databricks DevOps Engineer

Summary

Build and maintain Azure Databricks and cloud data pipelines using Terraform, CI/CD, and Azure DevOps; ensure scalable, secure, and high-performance data workflows.

About the job Azure Databricks DevOps Engineer

  • Databricks Management: Deploy, configure, and maintain Azure Databricks environments, ensuring scalability, security, and efficiency.
  • Infrastructure Automation: Implement and manage IaC using Terraform, ARM templates, or Bicep to automate cloud resource provisioning.
  • CI/CD Pipelines: Develop and manage CI/CD pipelines using tools like Azure DevOps, GitHub Actions, Jenkins to automate data pipeline deployments.
  • Monitoring & Logging: Set up and maintain monitoring solutions using Azure Monitor, Log Analytics, and Application Insights for proactive issue resolution.
  • Security & Compliance: Implement best practices for security, governance, and compliance, including RBAC, encryption, and network security policies.
  • Data Integration & Optimization: Work with Data Engineers to optimize ETL pipelines, ensuring high performance and cost efficiency.
  • Collaboration: Work closely with Data Scientists, Engineers, and Business Analysts to enable efficient data workflows.
  • Incident Management: Troubleshoot and resolve Databricks, Azure Kubernetes Services (AKS), and networking issues efficiently.
  • Documentation & Best Practices: Maintain technical documentation and establish best practices for Azure Databricks and DevOps processes.

Required Skills & Qualifications

  • Bachelors or Masters degree in Computer Science, IT, or a related field.
  • 5+ years of experience in DevOps, Cloud Engineering, or Data Engineering roles.
  • Strong hands-on experience with Azure Databricks, Azure Data Factory, and Azure Synapse Analytics.
  • Proficiency in Terraform, ARM Templates, or Bicep for infrastructure automation.
  • Experience with CI/CD tools such as Azure DevOps, GitHub Actions, or Jenkins.
  • Knowledge of Python, Scala, or PowerShell for automation and scripting.
  • Familiarity with containerization (Docker, Kubernetes, AKS).
  • Solid understanding of Azure networking, security, and identity management (IAM, RBAC, AAD).
  • Experience with monitoring and logging tools (Azure Monitor, Log Analytics, Prometheus, Grafana).
  • Strong problem-solving skills and ability to work in an Agile/Scrum environment.

Preferred Qualifications

  • Azure Certifications (e.g., AZ-400, AZ-104, DP-203, DP-900).
  • Experience with Big Data processing frameworks (Apache Spark, Delta Lake).
  • Understanding of ML Ops and working with machine learning models in Databricks.
  • Knowledge of Event-driven architectures (Azure Event Hubs, Kafka, Service Bus).

See also

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