About

Aleksandr Andreev

Lead Data Engineer with 9+ years building streaming, lakehouse and analytics platforms at production scale.

I work across the full data platform surface area: streaming pipelines, batch compute, table formats, orchestration, data quality and the tooling teams need to move faster without losing discipline.

In recent years I have also been building internal AI tooling, especially review and knowledge-assist systems grounded in real documentation rather than generic prompts.

This site is both a portfolio and a writing lab. I use it to publish essays, compact notes, and case studies about systems that are interesting because they have trade-offs, not because they have hype.

How I work

  • Prefer boring infrastructure when it scales operationally.
  • Make trade-offs explicit instead of hiding them in architecture diagrams.
  • Build platforms teams can actually adopt, not just admire.

Core stack

KafkaFlinkSparkAirflowdbtIcebergTrinoDuckDBPythonScalaTypeScriptKubernetes

Contact

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