IT runs on Data Engineering

Whether it’s AI, analytics, business intelligence, or process optimization — everything in IT revolves around data. We make your data work for you.

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Experts in extracting, storing, and processing data

From large-scale analytics to machine learning and data structuring, we have years of experience.
We power recommendation engines for streaming services such as NPO Start and Pathé Thuis.
For KLM and DZB Leiden, we trained a machine learning model to sort thousands of bolts from aircraft engines.
And during the COVID-19 pandemic, we structured complex GGD contact-tracing data from extensive questionnaires.

We work according to the FAIR data principles

Privacy and security by design

Solving complex challenges in our Innovation Lab

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Make experiences more personal, smarter, and better with data

What data do you have — and what can you collect? How do you bring together information from multiple sources while staying compliant with privacy laws?
From real-time data collection to relational storage and historical analysis, we make sure everything is structured, reliable, and ready for use.

With analytics, we help you understand how users interact with your app or platform — enabling personalized, enjoyable, and meaningful digital experiences. By structuring data properly, you can always rely on it as the foundation for future insights.

Explore the possibilities
Step 1

Data needs analysis

We assess what data you have and what data you need.

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Step 2

Data structure and tooling

We design the right data structures, tools, and storage mechanisms.

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Step 3

Data collection (ETL)

We gather data through Extract, Transform, Load (ETL) processes to ensure quality and consistency.

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Step 4

Structuring and accessibility

We organize the data and make it accessible for analytics, dashboards, and reporting.

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The impact of our Data Engineering

Aeternus Dawn Technology case header

A solid deal database for Aeternus

What looks simple is often more complex than it seems. Aeternus Corporate Finance wanted one central hub for all the acquisitions they have managed since their founding. Not a standard overview, but a visual, scalable database that works both internally and externally. At Dawn Technology, we developed a custom, scalable solution that grows with their business.

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Our programming languages

We use Python, R, Power Query, and SQL for our data solutions. This allows us to transform raw data into valuable insights. Whether it's dashboards, forecasts, or data migrations, we build data streams that are accurate and keep flowing.

Direct contact

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Direct contact with our experts

We believe in direct contact. That's why we'll immediately connect you with the right expert in your sector.

What our colleagues say

“We build robust data platforms that turn raw data into actionable insights — from data integration and modeling to scalable pipelines. Our data engineers ensure your organization is ready for intelligent solutions like AI, analytics, and automation — with data that’s reliable, secure, and accessible.”

Jasper Weeteling Chief Innovation Lab, Dawn Technology

Join our team

Want to build technology that works so seamlessly, people hardly notice it?

2 open vacancies

View our Data Engineering vacancies
iOS Ontwikkelaar
  • On site
 Hilversum
Android Developer
  • On site
 Hilversum
How does good data engineering support better decision-making?
By making data structured, reliable, and available in real time, we create a strong foundation for dashboards, analytics, and AI-powered insights.
Can you help set up a data warehouse or lakehouse?
Yes. We advise on the best approach — data warehouse, lake, or lakehouse — and implement it using modern cloud technologies such as Snowflake, Databricks, or Azure Synapse.
How do you ensure data pipelines remain scalable?
We design modular, event-driven ETL pipelines using tools like Apache Airflow and Azure Data Factory, with continuous performance monitoring.
Can you optimize or refactor existing data flows?
Absolutely. We review your current architecture and improve efficiency, cost, and reliability.
What does collaboration look like during a project?
We work iteratively with regular check-ins, clear expectations, and transparent progress reporting.