> Markdown version of [/jobs/ext/3641256-data-engineer-saas-healthcare](https://www.wearedevelopers.com/jobs/ext/3641256-data-engineer-saas-healthcare). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

---

# Data Engineer - Saas - healthcare

- **Company:** Harnham Bekijk Alle Vacatures
- **Location:** Eindhoven, Netherlands
- **Salary:** €5,333.0 - €5,417.0
- **Contract:** Permanent contract
- **Skills:** Data Analysis, Cloud Computing, Information Engineering, Data Governance, Data Infrastructure, Extract Transform Load (ETL), Data Warehousing, Performance Tuning, Sql Optimization, Data Management, Data Pipelines
- **Published:** October 9, 2026
- **Apply:** https://www.careerjet.nl/job/nlb42bccc3c0b54bf6655ef5248165fa96/eaa

## About the Role

Strong commercial experience in Data Engineering
Advanced SQL skills and experience with Python or PySpark
Experience building ETL pipelines and dimensional data models
Knowledge of modern cloud data platforms, lakehouse architectures, or similar environments
Understanding of data governance, security, and performance optimisation
Strong communication skills and the ability to work with both technical and non-technical stakeholders

## Description

This is an opportunity to join a growing data team where you will play a key role in building scalable data solutions that power business reporting, analytics, and decision-making. You'll work with modern cloud technologies and have direct influence on the evolution of the data platform.
The Company
They are a technology-led organisation investing heavily in data and analytics capabilities. With a strong focus on data quality, scalability, and governance, they are building a modern data environment to support business growth and innovation. Collaboration, ownership, and continuous improvement are central to their culture.
The Role
Design and develop scalable data pipelines and ETL processes
Build and maintain analytical data models and semantic layers
Create robust, secure, and high-performing datasets for reporting and analytics
Optimise data platform performance, reliability, and cost efficiency
Implement data governance, quality controls, and security best practices
Partner closely with analysts and stakeholders to translate business requirements into technical solutions