I'm Gabriel Landaeta Kranwinkel — a computer engineer who spent a decade in digital marketing, then came back to the technical side. For 5+ years I've designed end-to-end measurement: from the data layer in the browser to GA4, server-side GTM, and modeled BigQuery pipelines that analysts can actually trust.
I come from computer science, so the technical layer — JavaScript, data layers, network inspection, server-side logic — is home turf. But a decade running marketing and analytics teams taught me to translate it: to turn "what does the business actually want to measure?" into events, schemas and pipelines that survive contact with reality.
Today I work inside one of the most demanding environments there is — a heavily regulated banking measurement team — where every tag, every export and every consent signal has to be correct, governed and defensible. That discipline is what I bring to smaller projects too: setups that are clean, documented and built to last.
I'm equally comfortable owning a concept end-to-end or dropping in to audit, fix and hand back a healthier setup.
Own GA4 infrastructure and tracking concepts for a highly secure, heavily regulated banking environment — from concept and data layers through GTM implementation, data retrieval and processing for dashboarding. Architected the bank's full Dataform pipeline (flatten, clean, sessionize daily BigQuery exports) and manage privacy-compliant server-side GTM for Google Ads, Meta and LinkedIn.
Owned tracking tech and infrastructure for the whole group's sites and apps (GA360). Led the group-wide GA3→GA4 migration — 3,000+ unique events across 30+ websites and 12 mobile apps — plus server-side tagging, marketing pixel and API integrations, and custom JavaScript templates.
Drove the corporate Data-Driven Marketing project across six markets — Austria, Switzerland, Poland, Czech Republic, Hungary and Slovakia — optimizing programmatic, search and social spend while building measurement frameworks with local teams and agencies. Earlier, launched and ran the digital projects behind renault.es and dacia.es.
Raw daily GA4 exports land in BigQuery as deeply nested, event-level data — accurate, but expensive to query and slow for analysts. In a regulated bank, that data also has to be governed and auditable. I architected a Dataform pipeline to turn that firehose into trustworthy, analysis-ready tables.
Every team re-queried huge raw export tables, repeating expensive unnesting logic. Costs climbed, queries dragged, and definitions drifted between analysts.
Built a Dataform pipeline that flattens, cleans and sessionizes the daily exports into a single, documented source of truth — versioned, tested and scheduled, now migrating to dbt.
Significantly lower processing costs and query times for the whole team, with consistent metrics feeding dashboards — and a setup that holds up to the bank's privacy and governance standards.
A complete measurement ecosystem — data layer, GA4 and client- & server-side GTM — designed around what your business actually needs to measure.
A health check of your GA4, GTM and data layer: what's broken, what's double-counting, what's leaking — with a prioritized fix list.
Move tracking server-side with sGTM, Meta CAPI and consent-safe vendor integrations for better data quality and control.
Turn raw GA4 exports into clean, modeled, cost-efficient tables your analysts and dashboards can rely on.
GDPR-compliant CMP setup (Usercentrics, OneTrust, CookieBot) and Consent Mode — measurement done the privacy-first way.
GA3→GA4, client-side→server-side, or platform moves — planned and executed without losing data continuity.
Have a setup that needs building, fixing or auditing? Tell me a bit about it and I'll get back to you.