Hi, I'm GiGi.
I came into data through the side door — communication.
I grew up in Curaçao and trained as a communications specialist, with a research master's spent analysing how people actually talk — reading sentiment at scale, coding thousands of messages by hand, learning that a number is a message before it's a fact.
Web, SEO and marketing analytics pulled me closer to the data, until one day I was building the pipelines instead of just reading what came out of them. The instinct never changed: dig into the messy problem, find the smallest lever, push gently, and watch the system rearrange itself.
Today I work on the Microsoft data stack — Fabric, Power BI, Purview, Azure Data Services — with the people who own the data inside larger and semi-public organisations. I design architectures, audit ones already in flight, and write essays about the parts nobody documents.
One thing that shapes everything here: I care how the writing reads. Every essay is drafted and edited by hand, sentence by sentence, until it sounds like me — dry asides, em dashes and all. That punctuation isn't an AI tell; it's a habit from years of working across languages, and I'm not giving it up. If the prose comes out a little particular, that's on purpose.
What I stand for.
Three commitments I've put on every project for the last decade. They sound obvious. The reason I keep writing about them is that almost no one actually does the work.
The bridge between tech and the business is the work.
Senior BI/data specialists earn their fee in translation, not implementation. I gather requirements, turn them into clear technical plans, coordinate Agile or waterfall delivery — and I'm never afraid to roll up my sleeves and write the SQL alongside the team.
End-to-end means end-to-end.
Years of Power BI work, including the unglamorous part: training stakeholders to actually act on what the dashboard says. The better part of a decade on the Azure data stack, from on-prem migrations to greenfield cloud builds. I see the whole pipeline because I've built every segment of it.
Architectural rigour is a kindness to your future self.
Five years shaping enterprise data architectures, mostly to DAMA-DMBOK standards. The point isn't compliance — it's that governable, scalable, maintainable systems are the only ones still useful three years later.
The professional journey, abridged.
The full version is on LinkedIn. The interesting parts are below — the moments where something I thought I knew turned out to be wrong.
A step up in altitude — from solution architecture to a whole domain.
Started in August 2026, after a spring sabbatical — the first proper gap in thirteen years. The shift: from designing one system well to shaping how an entire domain's architecture holds together.
Architecting for a national rail programme — and translating AI risk for boards.
Safety-critical infrastructure by day; advisory work on governance and the EU AI Act alongside it. The lesson that keeps repeating: the hardest part is never the technology, it's the agreement underneath it.
Cut a BI estate's infrastructure cost by 44% — by deleting, not buying.
Power BI at scale, a broken warehouse rescued without a rebuild, and the first hands-on Fabric work once it landed in 2023. Earned the DAMA data-management credential somewhere in the middle.
Led a platform team through the modern-data-stack hype — and a pandemic.
Synapse, medallion, the data-mesh debate; Product Owner on a European Commission project under GDPR. Learned that you build the team before you build the platform.
Made a building talk — sensors, streams, and a digital twin.
Stream Analytics, Event Hub, Databricks, Kusto, and guest lectures on teaching data to city-makers. The edge taught me how much data lies to you before you clean it.
Crossed from marketing analytics into real data pipelines.
BIML, SSIS, PowerShell, Data Vault, and an on-prem warehouse hauled to Azure. Discovered that documenting a migration so humans can follow it is half the job.
Started reading data as a message, not a number.
Web, SEO and Google Analytics for small clients; a research master's spent coding thousands of messages in Python and SPSS. Curaçao to Amsterdam, with a comms degree and a growing suspicion that the data was where the real story lived.
Certified, for the curious.
Azure Data Engineer Associate
Power BI Data Analyst Associate
Fabric Analytics Engineer Associate
Professional Scrum Master I & II
Professional Scrum Product Owner I
DAMA-DMBOK Practitioner
BDS Data Science · Pro & Consulting
Purview Data Governance Specialty
The stack, today.
- ● Microsoft Fabric
- ● Power BI
- ● Azure Data Lake (Gen 2)
- ● OneLake
- ● Microsoft Purview
- ● Glossaries & lineage
- ● Stewardship workflows
- ● DAMA-DMBOK 2 framework
- ● Semantic models & DAX
- ● Tabular Editor 3
- ● Notebooks (Python · Spark)
- ● Synapse remnants, where alive
- ● Copilot in Fabric/Power BI
- ● Data Activator
- ● Real-Time Hub
- ● Metrics Layer (Public Preview)