MarTech & Growth Eng.

Attribution pipelines fail quietly. Nobody pages you when a campaign is under-reported by 8% — the dashboard just looks slightly wrong forever, until someone makes a budget decision on bad numbers. Most of my martech work is about closing that gap: making the data pipeline as rigorous as any other production system, instead of treating it as marketing's problem to eyeball.

I design forward from a strict event schema — stable event names, a real deduplication key, an explicit source of truth for timestamps — rather than backward from whatever report someone wants to see this quarter. Attribution windows, channel grouping, and CRM joins are all transformations on top of that stream, never patches to it. That one decision is what lets a pipeline survive a strategy change instead of needing a rewrite.

The other half of this work is the growth-engineering side: GTM, UTM discipline, Google Ads that actually turn a profit instead of just spending budget, and SEO/AEO work that compounds instead of chasing algorithm updates. Predictable traffic is a systems problem before it's a marketing problem, and that's the part I actually enjoy.