Data Engineering
I design pipelines that are observable, resilient, and boring in production.
Capabilities
| Capability | Description |
|---|---|
| Multi-source ingestion | Multiple formats normalized to a common schema with consistent metadata |
| Replay handling | Dedicated paths for historical data that preserve original timestamps |
| End-to-end traceability | Tenant and data-type metadata attached at ingestion, preserved through to storage |
| Operational metrics | Per-stage instrumentation: throughput, queue depth, processing time |
Design Principles
- Backpressure over dropping — Slowing upstream is visible; dropped data is invisible
- Idempotency where possible — Pipeline stages safe to retry
- Explicit routing over convention — Routing in config, not buried in code
- Observable by default — Instrumentation is part of initial design, not a later optimization
Related
- Distributed Wazuh SIEM Platform — Primary application of these patterns
- Observability Platform — How I monitor pipelines