I design and build data platforms.

I have experience within a wide variety of technologies, my main focus being data engineering. Having started my career as a SAP BI developer, I later pivoted to the Microsoft stack, with Azure Databricks — in which I achieved the highest accreditation in the Databricks championship — becoming my main focus.

After nine years, and with the rise of AI — more notably, LLMs — I decided to pivot in order to become an expert within this new field. Now, I combine my knowledge in both Data and AI to achieve the best possible business result.

My question-first approach allows me to facilitate between stakeholders & IT, allowing me to design the specifications and ensure they’re executed within the constraints, time, and budget presented. Either by technically diving deep (implementing) myself, or with the help of my colleagues or team.

Email me

Experience

and others

Selected work

Aquafin 2026–present

Data engineering and platform setup

Data engineer

The role includes regular data engineering support for the business.

Alongside that, I’m developing the Aquafin loader, a data loading framework built around configuration and Python. Every transformation can be developed, tested and validated before production. The aim is to go beyond NIS2 compliance, with validation that also covers data quality and correctness. I also work on the Azure Databricks platform and on automated deployments.

Platform: Azure Databricks
Focus: Data pipelines, Auto Loader, incremental ingestion
Delivery: Azure DevOps CI/CD, Databricks Asset Bundles, automated testing

Ascendis Pharma 2025

Data platform design and implementation

Data engineer

As part of the Dynamics 365 migration, I designed and implemented the data platform end to end on Azure Databricks.

This included Delta Lake pipelines, Unity Catalog governance and access controls, and CI/CD through Azure DevOps with Databricks Asset Bundles.

Platform: Azure Databricks
Focus: Delta Lake pipelines, Unity Catalog governance, access control
Delivery: Azure DevOps CI/CD, Databricks Asset Bundles

Bridgestone 2024–2025

Unity Catalog and reporting migration

Lead data engineer

I migrated legacy reporting on SQL Server and Tableau to Azure Databricks and Power BI, and separately moved the platform from Hive Metastore to Unity Catalog.

Besides the migrations, I set up Azure DevOps CI/CD with automated testing and advised on data platform architecture, Azure infrastructure and cost optimisation.

Platform: Azure Databricks
Focus: Hive Metastore to Unity Catalog, Power BI reporting migration, cost optimisation
Delivery: Azure DevOps CI/CD, automated testing

Aquafin 2023–2024

A shared loading framework

Azure data engineer

During Aquafin’s SAP S/4HANA migration, I built an Azure Databricks framework for incremental loading and slowly changing dimensions and was the single point of contact for data engineering.

The framework is used by 8 engineers.

Platform: Azure Databricks
Focus: Azure Data Lake, Azure Data Factory, reusable ingestion, incremental loading, SCD
Delivery: Azure DevOps CI/CD, automated testing

Food manufacturing

Sales process in Power Apps

For a food manufacturer, I redesigned the whole sales process in Power Apps, with SharePoint for data and documents and Power Automate for workflows.

Platform: Microsoft Power Platform
Focus: Power Apps, SharePoint lists and document libraries, Power Automate workflows

Services

Example lakehouse structureAzure Databricks

Sources

Business systems
Files
Event streams

Ingestion

Auto Loader
CDC
Metadata-driven loads

Unity CatalogPermissions & lineage

BronzeSource data

SilverValidated data

GoldData models

Used by

Power BISemantic models
AI workflows
Applications

Deployment & checks

TerraformCI/CD · Databricks Asset BundlesData quality & freshness

Data architecture

Azure Databricks & Microsoft Fabric
Lakehouse design, medallion architecture & platform migrations
Unity Catalog: governance, lineage & permissions
Dimensional & Data Vault modelling
Power BI semantic models
Azure infrastructure as code with Terraform

Data engineering

Python, PySpark & SQL pipelines
Lakeflow Spark Declarative Pipelines
Auto Loader, Structured Streaming & Event Hubs
Metadata-driven ingestion & schema management
Incremental loading, CDC & SCD frameworks
PySpark & Delta Lake performance tuning
CI/CD with Databricks Asset Bundles
Data quality, freshness checks & automated tests

Data visualisation

Power BI reports, dashboards & interactive visuals
DAX measures & semantic models
Star-schema modelling
Power Query (M) & data preparation
Row-level security & workspace permissions
Refresh, publishing & Fabric deployment pipelines

Power Platform

Power Apps canvas applications & Power Fx
SharePoint lists, document libraries & access control
Dataverse & Microsoft 365 integration
Power Automate workflows, requests & approvals
Forms, Teams & Outlook integrations

AI applications

Retrieval & ranking with pgvector / HNSW
LLM orchestration & agent workflows
Structured outputs & prompt/schema versioning
Retrieval, ranking & LLM evaluation
FastAPI, PostgreSQL & application access control

About

I started at delaware in 2017 as a data and analytics consultant. Those first years were mostly SAP: BI projects, HR and payroll integrations, SAP SuccessFactors and SAP Analytics Cloud.

At UZ Gent, I worked on the requirements for the hospital’s HR and payroll integrations and reporting, trained users in SAP Analytics Cloud and coached colleagues on SAP Cloud Platform.

Later, I moved into data engineering on the Microsoft stack, mainly Azure Databricks. I’ve been independent since 2022, working on data engineering, platform architecture and AI engineering. You work directly with me.

2026–present: AquafinData engineering and platform design
2024–2025: Bridgestone & AscendisData engineering and platform design
2023–2024: AquafinAzure data engineer
2022–present: De Geest ConsultingData engineering, AI engineering & architecture
2017–2022: delawareSAP and business intelligence consultant