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a-sydelov/README.md

Andrey Sydelov

Staff Data Platform Engineer working across modern data platforms, governance, observability, and AI/ML enablement.

I design and build cloud-native data and ML foundations end to end. This includes platform architecture, warehouse and lakehouse systems, batch and streaming pipelines, data quality, monitoring, metric ownership, and access controls.

My work sits at the intersection of trusted data systems and the enablement layer for AI/ML use cases. It also includes model-ready datasets, RAG workflows, and operational foundations around inference and deployment control.

Focus areas

  • data platforms: streaming, governance, observability
  • warehouse and lakehouse architecture
  • real-time and CDC pipelines
  • data quality, lineage, and metric ownership
  • AI/ML enablement: model-ready data, RAG, MLflow foundations
  • service architecture around inference, rollout control, and operational visibility

Links

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  1. ai-service-skeleton ai-service-skeleton Public

    Practical skeleton for ML/AI services with controlled rollout, primary/shadow serving, observability, and cutover/rollback.

    Python 1