Cloudops

Area(s) of responsibility

Job Description: Cloud Data Platform Engineer / SRE (Azure | Databricks | Fabric | Unity Catalog)

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Key Responsibilities

• Cloud Platform Operations
• Manage and optimize Azure workloads—ADLS, VNets, Key Vault, ADF, Synapse, Fabric, Databricks.
• Configure and maintain Databricks clusters, jobs, DLT pipelines, Delta Lake storage, and Unity Catalog policies.
• Operationalize Fabric Lakehouses, Pipelines, Warehouses, and Semantic Models for production workloads.
• Ensure robust platform governance across environments (DEV–QA–UAT–PROD).
• Infrastructure as Code & CI/CD
• Build and maintain Terraform/Bicep templates for environment provisioning and configuration.
• Develop end-to-end CI/CD pipelines for Databricks, Fabric, and Azure components (ADO/GitHub).
• Automate deployment of notebooks, workflows, access policies, networking components, and Fabric artifacts.
• Enforce version control, release governance, and quality gates.
• FinOps, Cost Management & Capacity Planning
• Implement FinOps dashboards, alerts, budgets, and spend governance practices.
• Perform Databricks and Fabric cost optimization—cluster sizing, autoscaling, idle management, job tuning.
• Conduct capacity planning for compute, storage, Fabric engines, and Databricks workloads.
• Develop cost-saving recommendations and automated consumption monitoring.
• Environment Management, Security & Governance
• Provision and manage Azure data environments with consistent policies and naming standards.
• Configure RBAC, ACLs, Unity Catalog grants, service principals, network security, Managed Identities.
• Implement governance standards for data access, lineage, audit logging, compliance, and risk mitigation.
• Ensure secure connectivity using Private Endpoints, VNET integration, and enterprise IAM controls.
• Monitoring, Observability & Platform Reliability (SRE)
• Implement monitoring and alerting using Azure Monitor, Log Analytics, Databricks Metrics, Fabric Admin APIs.
• Build runbooks, dashboards, and automated remediation workflows for platform reliability.
• Conduct performance tuning of data workloads, Fabric pipelines, Databricks jobs, and storage layers.
• Lead incident management, root cause analysis, and environment stabilization efforts.

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Required Skills & Experience

• 6–12 years in cloud data engineering, SRE, or platform engineering roles.
• Strong hands-on expertise with:
• Azure Data Services (ADLS, ADF, Synapse, Key Vault, VNets)
• Azure Databricks (clusters, jobs, Delta Lake, DLT, Unity Catalog)
• Microsoft Fabric (Lakehouse, Pipelines, Warehouse, Dataflows)
• Unity Catalog governance (catalogs, schemas, access policies, lineage)
• Strong scripting and automation experience: Python, PowerShell, Bash, SQL, PySpark.
• Experience with Terraform/Bicep for IaC.
• Strong knowledge of Azure DevOps or GitHub Actions CI/CD pipelines.
• Proven FinOps experience with cost governance and optimization across cloud workloads.
• Experience in SRE practices—SLIs, SLOs, operational readiness, automated recovery.

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Preferred Qualifications

• Certifications in Azure Data Engineer, Azure DevOps Engineer, Databricks Data Engineer, FinOps Practitioner.
• Experience in highly regulated environments (BFSI, Healthcare, Retail).
• Understanding of zero-trust security models.