Services
From the first DAG to a self-service platform
Apache Airflow: Adoption & Migration
Introducing Airflow as your central orchestration tool, replacing home-grown ETL and migrating to Airflow 3 — with clean DAG conventions, monitoring and CI/CD.
Self-Service Data Platforms
Data platforms built on Amazon Athena, Glue and S3 with dbt and Spark, where teams model, analyze and visualize data in Superset on their own — with Databricks where it fits.
Data Warehouse & Customer Data Platform
Data warehouses and customer data platforms on Amazon Redshift — including integrations with sources such as Salesforce or Adobe Marketing Cloud.
Privacy Engineering & GDPR
Data protection built into the platform rather than checked afterward: automated handling of data subject requests, clean access separation and data governance — with the GDPR and the EU AI Act in mind.
AI & RAG on Company Data
Internal chatbots and RAG applications built with LangChain on your company's data — with multi-tenant access control, so users only see what they're allowed to see.
Cloud Infrastructure & IaC
Reproducible data platform infrastructure on AWS with Terraform, Kubernetes (EKS) and Docker — versioned, automated and safe to change.
How it works
How we work together
Every engagement follows the same three phases, adapted to your team and your existing setup.
Assessment
I get to know your existing data flows, tools and requirements, and identify where the biggest levers are.
Build with your team
I work inside your team, from architecture to production code, in small, reviewable steps.
Handover & enablement
Documentation, conventions and knowledge transfer, so your team can run and evolve the platform on its own.
Technology
Built on a proven stack
- Apache Airflow
- Python
- SQL
- AWS
- Amazon Redshift
- Amazon Athena
- dbt
- Spark
- Kubernetes
- Terraform
- Docker
- Superset
- Databricks
- Scala
- Java
- FastAPI
Not sure where to start?
Get in touch and we'll figure out together which service fits your situation best.
Get in touch