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Data Engineering
Data engineering for quant workflows means building systems that ingest, validate, store, and serve market data reliably. I write about the infrastructure choices, data modeling decisions, and operational practices that keep financial data pipelines running correctly. Getting this layer wrong corrupts everything downstream, from research to live trading.
2026-05
Quant
From Hypothesis to Production: A Quant's Productivity Toolkit
Productivity in quantitative work isn’t about doing things faster. It’s about knowing when to stop. A walkthrough of the tools and stages I use to take a trading strategy hypothesis from …