Senior Databricks Platform Engineer Azure Cloud & Data Operations

Role Overview: As a Senior Databricks Platform Engineer at CirrusLabs, you will be responsible for supporting the design, operational enablement, modernization, and ongoing support of enterprise Databricks platforms and associated data processing environments. You will collaborate closely with cloud platform teams, DevOps organizations, infrastructure engineering teams, application modernization groups, and data and analytics stakeholders. Your role will require a strong awareness of how Databricks modernization activities impact existing CI/CD pipelines, automation frameworks, operational governance, and enterprise cloud platform standards. Key Responsibilities: - Support architecture and operational engineering across enterprise Databricks environments - Design and maintain scalable Lakehouse, Delta Lake, and Unity Catalog solutions - Support administration of Databricks Workspaces, Jobs, Notebooks, and Clusters - Optimize Spark workloads, cluster configurations, and platform performance - Support batch and streaming data processing workloads - Assist with multi-environment platform management across Dev, QA, and Production Platform Integration & DevOps Alignment: - Support integration of Databricks platforms with Azure-native ecosystems and enterprise applications - Collaborate with platform and DevOps teams to align Databricks activities with existing CI/CD and automation standards - Support deployment workflows utilizing GitHub, Azure DevOps, and Infrastructure as Code frameworks - Help ensure modernization activities do not disrupt existing automated deployment pipelines and operational processes Governance, Reliability & Platform Support: - Support governance, access management, monitoring, logging, and operational security practices - Assist with implementation of RBAC, lineage, encryption, and platform governance controls - Participate in troubleshooting, operational support, and root cause analysis activities - Contribute to documentation, operational standards, and platform best practices Required Qualifications: - 6+ years of experience within cloud, platform engineering, data engineering, or enterprise analytics ecosystems - 3+ years of hands-on experience supporting enterprise Databricks environments - Strong experience with Delta Lake, Unity Catalog, Spark workloads, cluster operations, and Databricks Workspaces - Experience with Azure cloud services and cloud-native platform concepts - Familiarity with Azure DevOps, GitHub workflows, CI/CD pipeline concepts, and deployment automation - Experience supporting APIs, distributed application integrations, and enterprise data platforms - Strong troubleshooting and operational support capabilities - Strong communication and stakeholder collaboration skills Preferred Qualifications: - Experience with PySpark, Python, SQL, Spark SQL, Scala - Familiarity with AKS/Kubernetes, Terraform, Bicep, Infrastructure as Code practices - Experience with Azure Data Lake, Event Hub, streaming architectures, enterprise analytics environments - Familiarity with monitoring and observability platforms such as Azure Monitor, Datadog - Exposure to enterprise modernization and cloud migration initiatives Company Additional Details (if present): You will be joining a globally recognized consulting and technology organization supporting enterprise-scale transformation initiatives across Azure cloud platforms, platform engineering, DevOps and automation, large-scale data modernization, and Analytics and AI-enabled ecosystems. This role provides the opportunity to help shape and support modern enterprise data platform operations within a highly collaborative global engineering environment. Role Overview: As a Senior Databricks Platform Engineer at CirrusLabs, you will be responsible for supporting the design, operational enablement, modernization, and ongoing support of enterprise Databricks platforms and associated data processing environments. You will collaborate closely with cloud platform teams, DevOps organizations, infrastructure engineering teams, application modernization groups, and data and analytics stakeholders. Your role will require a strong awareness of how Databricks modernization activities impact existing CI/CD pipelines, automation frameworks, operational governance, and enterprise cloud platform standards. Key Responsibilities: - Support architecture and operational engineering across enterprise Databricks environments - Design and maintain scalable Lakehouse, Delta Lake, and Unity Catalog solutions - Support administration of Databricks Workspaces, Jobs, Notebooks, and Clusters - Optimize Spark workloads, cluster configurations, and platform performance - Support batch and streaming data processing workloads - Assist with multi-environment platform management across Dev, QA, and Production Platform Integration & DevOps Alignment: - Support integration of Databricks platforms with Azure-native ecosystems and enterprise applications - Collaborate