Architect, design, and implement distributed data services to support largescale data processing
Lead the orchestration and optimization of high-volume ETL pipelines for timeseries and telemetry
Oversee and manage Kubernetes-native autoscaling services to efficiently handle dynamic workloads.
Architect and implement data threshold–based alerting pipelines, and partner with avionics
Continuously research, evaluate, and adopt new data ingestion, storage, and retrieval technologies

🎯 Requirements

Bachelor’s degree in Computer Science or Computer Engineering.
12 months of experience with Python, AWS, Data Governance, ETL Pipeline, and Docker.

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