Microsoft Fabric Engineer (Real-Time Intelligence & Time Series Data)
Role Overview
Implement Real-Time Intelligence solutions for time-series data processing.
Architect, design, and optimise real-time data pipelines in Microsoft Fabric Real-Time Analytics.
The role focuses on Microsoft Fabric and Azure Data Explorer for high-volume streaming data.
Key Skills for This Role
Full Job Posting
Role Overview
Implement Real-Time Intelligence solutions for time-series data processing.
Architect, design, and optimise real-time data pipelines in Microsoft Fabric Real-Time Analytics.
The role focuses on Microsoft Fabric and Azure Data Explorer for high-volume streaming data.
Implementation and Data Engineering
- Design and implement real-time ingestion and processing pipelines using Fabric Real-Time Analytics or Azure Data Explorer.
- Develop scalable processing solutions for time-series data from IoT devices, sensors, and telemetry.
- Optimise data models for storage, querying, and analytics.
- Build Kusto Query Language queries for time-series analysis.
- Integrate event streams such as IoT Hub, Event Hubs, and Kafka.
- Implement data transformation, enrichment, and aggregation for analytics and dashboards.
Performance and Analytics
- Tune Kusto queries and Azure Data Explorer clusters for large-scale time-series workloads.
- Implement retention, indexing, partitioning, and archival strategies.
- Ensure high availability and fault tolerance in streaming architectures.
- Enable real-time insights through Power BI, dashboards, alerts, and anomaly detection.
- Implement real-time triggers, alerts, and automated responses based on streaming insights.
- Collaborate with Data Science and BI teams on predictive analytics and machine learning.
Required Skills and Qualifications
- 3+ years of experience in Microsoft Fabric, Real-Time Analytics, or Azure Data Explorer.
- Kusto Query Language and Azure Data Explorer data modeling are listed as good to have.
- Hands-on experience with event-driven architectures, data streaming, and IoT analytics.
- Experience integrating Event Hubs, IoT Hub, Kafka, or other real-time sources.
- Knowledge of time-series techniques, downsampling, and anomaly detection.
- Familiarity with Synapse, Power BI, Databricks, or other analytics platforms.
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