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PythonAzureKubernetesAirflow
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Job Description
I am looking for ongoing technical job support in a production Azure data engineering environment involving large-scale telemetry, hardware reliability analysis, and anomaly detection workflows.
The role requires hands-on guidance and review support in the following areas:
Core Technical Areas
- PySpark (large-scale data filtering, aggregation, joins, optimization)
- Delta & Parquet datasets
- Azure Data Explorer (Kusto / KQL queries)
- VM-level RCA and fault code correlation
- Rack telemetry signal exploration (GPU, NIC, power, temperature, ECC, PCIe)
- Hardware signal interpretation and component mapping
- Statistical anomaly detection (z-score, baseline comparison, fleet analysis)
Infrastructure & Platform Understanding
- Airflow DAG structure and job orchestration
- Kubernetes runtime basics
- Production data pipelines
- Telemetry ingestion workflows
- Correlating VM-level failures with hardware-level signals
Contract duration of 1 to 3 months. with 30 hours per week.
Mandatory skills:
Python, Data Science, Data Analysis, Statistics, Machine Learning
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