Microsoft Data Platform Administrator

Working at Freudenberg: We will wow your world!

Responsibilities:

• Design, build, and operate a secure, scalable, AI‑ready data and analytics platform on Microsoft Azure and Microsoft Fabric, including OneLake, Lakehouse, and Warehouse components.
• Administer and optimize Azure and Fabric platform resources including subscriptions, resource groups, RBAC, Azure Policies, and Fabric capacities (F SKUs), workspaces, and item governance.
• Manage storage and compute layers across the platform covering ADLS Gen2, Delta Lake, Lakehouse/Warehouse, SQL pools, and Spark runtime and capacity settings.
• Enable and operate data ingestion and transformation services using Azure Data Factory, Synapse Pipelines, Fabric Data Factory, and Dataflows Gen2, focusing on platform configuration, reliability, and standards (no pipeline business logic).
• Establish platform reliability and operational excellence including monitoring, alerting, autoscaling, performance tuning, cost control, tagging, chargeback/showback, and capacity optimization.
• Harden platform security end to end leveraging Entra ID (Azure AD), PIM, conditional access, managed identities, Key Vault, private endpoints, encryption, and network isolation.
• Implement governance, compliance, and data protection controls using Microsoft Purview (catalog, lineage, classification), DLP, sensitivity labels, retention policies, and auditing.
• Enable AI/ML and advanced analytics workloads by integrating Azure Machine Learning and Fabric ML experiences, including feature stores, registries, compute access, and inference endpoints from a platform perspective.
• Oversee CI/CD and lifecycle management for analytics and data platform artifacts including Fabric Git integration, Azure Repos/GitHub, branching strategies, automated deployments, and environment promotion.
• Act as tenant and workspace administrator and platform enabler for Fabric and Power BI (capacity settings, gateways, semantic models, refresh, RLS/OLS), while collaborating cross‑functionally, defining best practices, and coaching teams on platform usage.

Qualifications:

• Azure platform administration: Entra ID, RBAC, Azure Policy / Blueprints, subscription & resource group management, Cost Management, automation standards.
• Microsoft Fabric administration (hands‑on): Capacities (F SKUs), workspaces, Lakehouse, Warehouse, OneLake, Shortcuts, Notebooks, Fabric Data Factory and Dataflows Gen2.
• Security‑by‑design for data platforms: Network segmentation, Private Endpoints, Key Vault / CMK, managed identities, secret rotation, DLP and encryption.
• Governance & compliance controls: Microsoft Purview (catalog, lineage, classification), RLS/OLS, sensitivity labels, audit logging, data residency & privacy requirements.
• Power BI & Fabric tenant administration: Tenant settings, gateways, semantic model governance, incremental refresh, Direct Lake / DirectQuery, deployment pipelines.
• Storage & compute operations for analytics platforms: ADLS Gen2, Delta Lake, Spark runtimes, SQL (Synapse / Fabric Warehouse), partitioning, caching, performance tuning.
• Observability and operational excellence: Azure Monitor, Log Analytics / KQL, Fabric capacity metrics, refresh diagnostics, query performance, cost/performance optimization.
• DevOps and container platform operations: Git-based workflows, YAML pipelines (Azure DevOps / GitHub Actions), environment promotion, release automation, and AKS platform operations (cluster configuration, scaling, upgrades, workload isolation).
• MLOps / AI platform enablement: Integration with Azure ML / Fabric ML: model lifecycle, feature stores, pipelines, registries, and governance (platform perspective).
• Scripting, automation & infrastructure as code: PowerShell / Azure CLI, Python / SQL scripting, IaC (Bicep / Terraform) for repeatable, governed platform changes.
• FinOps-aware platform administration: Cost attribution, capacity optimization, showback/chargeback models.
• Experience with adjacent data & streaming platforms: Azure Databricks, Event Hubs / Kafka, or similar large-scale data services.
• Advanced Kubernetes ecosystem capabilities: Ingress controllers, service mesh (e.g. Istio/Linkerd), workload identity, secrets integration, and cluster‑level security hardening.
• Platform leadership & enablement: Experience leading platform rollouts, defining standards and guardrails, mentoring engineering teams.

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