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Niche Microsoft Fabric MLOps platform role with specialized Azure skills reduces applicant density.
Requires Azure Fabric-specific MLOps and enterprise data-platform experience, limiting cross-industry transferability.
Multiple mandatory Azure, Fabric, MLOps, CI/CD, and security requirements create strict technical shortlisting filters.
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Build and operate Microsoft Fabric-based data science and MLOps platforms enabling production batch prediction and forecasting pipelines with automated CI/CD and monitoring.
Own end-to-end technical delivery of governed environments, pipeline templates, orchestration, data quality gates, security controls, and observability for unattended, reproducible execution.
Produce operational runbooks and documentation to enable client IT and data science teams to maintain and operate the platform post-handoff.
5+ years of experience in data engineering, ML engineering, or MLOps with production delivery on Microsoft Azure.
Hands-on experience with Microsoft Fabric components including workspaces, OneLake, Lakehouse, Warehouses, RBAC, notebooks, and deployment pipelines; experience with Synapse or Databricks plus Fabric exposure accepted.
Strong Python and SQL coding skills for production-grade reusable and testable pipelines.
Bachelor's degree in Computer Science, Data Science, Engineering, or related field.
Experienced in enterprise-scale ML platform engineering focusing on infrastructure, operationalization, and governance rather than pure model development.
Familiar with Microsoft Fabric ecosystem and associated Azure security and deployment tools (Entra ID, managed identities, Azure Key Vault, Azure DevOps).
Strong operator mindset with ability to produce clear documentation, runbooks, and design artifacts supporting client handovers and ongoing platform support.