Digital Analytics & Tracking Architecture · Berlin

I build tracking infrastructure that actually holds up in production.

I'm Gabriel Landaeta Kranwinkel, a computer engineer who spent a decade in digital marketing before coming back to the technical side. For the last 5+ years I've designed end-to-end measurement: from the data layer in the browser, through GA4 and server-side GTM, to the BigQuery pipelines analysts can actually trust.

5+
Years in tracking
architecture
3,000+
Unique events
migrated to GA4
30+
Websites &
12 mobile apps
GDPR
Privacy-first
by default

Engineering depth, marketer's clarity.

I come from computer science, so the technical layer is home turf: JavaScript, data layers, network inspection, server-side logic. 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 the measurement team of a heavily regulated bank, where every tag, every export, and every consent signal has to be correct and defensible. That kind of discipline goes into smaller projects too: clean setups, documented properly, made to last.

Happy taking a project from scratch, or dropping in to audit and fix what's already there.

Spanish native English C2 German B2 French B1

Tracking & Analytics

GA4GA360 GTM — client-sideGTM — server-side Measurement ProtocolMeta CAPI Consent Mode

Data Architecture & Cloud

BigQueryDataform dbtFirestore Looker

Privacy & Consent

GDPRUsercentrics OneTrustCookieBot

Web & Debugging

JavaScriptHTML Data LayersDev Tools Network Inspection

Where I've done the work.

2024 — Present

Senior Specialist, Digital Measurement

Commerzbank AG (via REACHX) · Berlin

Own the GA4 infrastructure and tracking concepts for a heavily regulated banking environment. That covers everything from data layer design and GTM implementation through to the data processing that makes the data usable downstream. I architected the bank's Dataform pipeline (flattens, cleans, and sessionizes the daily BigQuery exports) and run the server-side GTM setup that lets marketing teams deploy Google Ads, Meta, and LinkedIn tags inside the bank's privacy constraints.

2020 — 2024

Digital Tracking Specialist · Product Analytics

HelloFresh Group · Berlin

Owned tracking tech and infrastructure for the whole group's sites and apps on GA360. Led the group-wide GA3 to GA4 migration: 3,000+ unique events across 30+ websites and 12 mobile apps. Also handled server-side tagging, marketing pixel and API integrations, and custom JavaScript templates for both client- and server-side GTM.

2017 — 2022

Data-Driven Marketing Consultant

Groupe Renault · Madrid

Ran 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. Before that, launched and ran the digital projects behind renault.es and dacia.es.

From no data strategy to ~80% lower BigQuery costs.

When the team shifted from the GA interface and Data Studio to BigQuery, the data showed up but the strategy didn't. Analysts were writing complex queries straight off the raw event-level exports, costs grew every month, and the same metric meant different things on different dashboards. I came in to fix that. First the data strategy and the structure, then the technical layer to back it up: the Dataform pipeline that now sits between raw exports and everyone who uses them.

Problem

BigQuery without a plan

The team had moved from the GA interface to raw BigQuery exports without a data strategy. Analysts hit the firehose directly with complex, expensive queries. Costs grew. The same metric meant different things to different people.

Approach

Strategy first, then the pipeline

I defined the data model and shared metric definitions first, then architected the Dataform pipeline to back them. It flattens, cleans, and sessionizes the daily exports into documented, analysis-ready tables. Currently migrating it to dbt.

Result

~80% lower query costs

Monthly BigQuery costs dropped by roughly 80%, with faster, simpler queries on top. The less measurable win: analysts spend their time on analysis instead of wrestling with raw GA4 schemas.

What you can hire me for.

/01

Tracking setup from scratch

A complete measurement ecosystem — data layer, GA4 and client- & server-side GTM — designed around what your business actually needs to measure.

/02

Analytics & tracking audits

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.

/03

Server-side tagging

Move tracking server-side with sGTM, Meta CAPI and consent-safe vendor integrations for better data quality and control.

/04

BigQuery & Dataform pipelines

Turn raw GA4 exports into clean, modeled, cost-efficient tables your analysts and dashboards can rely on.

/05

Consent & privacy

GDPR-compliant CMP setup (Usercentrics, OneTrust, CookieBot) and Consent Mode — measurement done the privacy-first way.

/06

Migrations

Two flavors: replatforming a website without losing tracking continuity, or moving from one analytics or tag-management setup to another. Planned so the data history stays intact.

05 — Contact

Let's talk tracking.

Have a setup that needs building, fixing or auditing? Tell me a bit about it and I'll get back to you.

LinkedIn/in/mrgelk
BasedBerlin, Germany