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Specialized Microsoft Fabric and MLOps requirements limit candidates despite mid-level seniority.
MLOps and Fabric skills are transferable across industries but remain moderately niche.
Multiple mandatory technical filters including 5+ years, Fabric/Azure, CI/CD, Python, and MLOps make shortlisting strict.
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Build and manage Microsoft Fabric-based MLOps platforms enabling data science teams to operationalize batch prediction and forecasting workflows.
Develop and maintain pipelines, CI/CD automation, data quality gates, and observability ensuring reliable, unattended production runs.
Own significant technical workstreams end-to-end, delivering governed environments, runbooks, and knowledge transfer to client teams.
5+ years in data engineering, machine learning engineering, or MLOps with production delivery on Microsoft Azure.
Hands-on experience with Microsoft Fabric components: workspaces, OneLake, Lakehouse/Warehouse, Notebooks, RBAC, deployment pipelines.
Strong Python and SQL skills with production-grade coding for reusable, tested, scheduled execution.
Bachelor's degree in Computer Science, Data Science, Engineering, or related field.
Experienced in operationalizing production batch scoring and forecasting with failure handling and retries on Microsoft Fabric or similar platforms.
Skilled in CI/CD and orchestration tools like Azure DevOps, GitHub Actions, Fabric Data Pipelines, or Airflow with strong MLOps discipline.
Comfortable working across US Eastern business hours and producing clear operational documentation for client IT/data science teams.