About the job Azure Databricks DevOps Engineer
Azure Databricks DevOps Engineer
Key Responsibilities:
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Databricks Management: Deploy, configure, and maintain Azure Databricks environments, ensuring scalability, security, and efficiency.
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Infrastructure Automation: Implement and manage IaC using Terraform, ARM templates, or Bicep to automate cloud resource provisioning.
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CI/CD Pipelines: Develop and manage CI/CD pipelines using tools like Azure DevOps, GitHub Actions, Jenkins to automate data pipeline deployments.
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Monitoring & Logging: Set up and maintain monitoring solutions using Azure Monitor, Log Analytics, and Application Insights for proactive issue resolution.
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Security & Compliance: Implement best practices for security, governance, and compliance, including RBAC, encryption, and network security policies.
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Data Integration & Optimization: Work with Data Engineers to optimize ETL pipelines, ensuring high performance and cost efficiency.
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Collaboration: Work closely with Data Scientists, Engineers, and Business Analysts to enable efficient data workflows.
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Incident Management: Troubleshoot and resolve Databricks, Azure Kubernetes Services (AKS), and networking issues efficiently.
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Documentation & Best Practices: Maintain technical documentation and establish best practices for Azure Databricks and DevOps processes.
Required Skills & Qualifications:
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Bachelors or Masters degree in Computer Science, IT, or a related field.
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5+ years of experience in DevOps, Cloud Engineering, or Data Engineering roles.
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Strong hands-on experience with Azure Databricks, Azure Data Factory, and Azure Synapse Analytics.
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Proficiency in Terraform, ARM Templates, or Bicep for infrastructure automation.
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Experience with CI/CD tools such as Azure DevOps, GitHub Actions, or Jenkins.
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Knowledge of Python, Scala, or PowerShell for automation and scripting.
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Familiarity with containerization (Docker, Kubernetes, AKS).
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Solid understanding of Azure networking, security, and identity management (IAM, RBAC, AAD).
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Experience with monitoring and logging tools (Azure Monitor, Log Analytics, Prometheus, Grafana).
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Strong problem-solving skills and ability to work in an Agile/Scrum environment.
Preferred Qualifications:
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Azure Certifications (e.g., AZ-400, AZ-104, DP-203, DP-900).
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Experience with Big Data processing frameworks (Apache Spark, Delta Lake).
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Understanding of ML Ops and working with machine learning models in Databricks.
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Knowledge of Event-driven architectures (Azure Event Hubs, Kafka, Service Bus).