Design and build the data pipelines that turn flow logs, cloud configuration, and Kubernetes data
Own these pipelines in production: reliability, monitoring, data quality, and cost
Make attribution provable: handle recycled identities, late and out-of-order data, and the places
Engineer for cost: partitioning, incremental processing, and sampling that keep a scan-heavy
Work closely with the engineers behind our Kubernetes collectors and graph engine, using AI tooling

🎯 Requirements

4+ years of experience in a Data Engineering role, building and running data pipelines over
Experience building pipelines over raw cloud or network telemetry at scale (VPC Flow Logs
Deep SQL: window functions, temporal joins, partitioning, and scan-cost control
Cloud-native production experience (AWS or Azure)
Experience owning a data pipeline end to end: design, production, operation, and cost
Kubernetes familiarity (Pods, Services, networking) - advantage

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