A lean data ingestion engine for Mindzo Investment Union
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We built an internal, high-throughput data parser for Mindzo Investment Union.

The goal for Mindzo Investment Union was simple: replace a bloated Python ETL with a minimalist Go-based pipeline that maps complex, multi-format filing data into clean, structured tables in sub-50ms.

Any tips on maintaining schema flexibility without the performance hit?

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