Cloudops

Area(s) of Responsibility

Key Responsibilities

1. 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).
2. 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.
3. 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.
4. 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.
5. 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.