Data Engineer

We are now looking for an experienced Data Engineer to build and evolve scalable data platforms and pipelines that support the

analysis and validation of complex technical systems.

You will work with Python, SQL, PySpark, and distributed data processing, transforming large volumes of data into structured,

reliable, and accessible information.

This is the right role for someone who enjoys building robust data infrastructure and wants to see how well-designed data

pipelines can enable smarter, faster, and more automated system validation.

Your main responsibility will be to design and develop the data pipelines, processing capabilities, and data models needed to make

complex datasets useful for analysis, system validation, and automated regression testing.

The role sits at the intersection of data engineering and system validation, where data quality, traceability, reproducibility,

and performance are essential.

While an understanding of testing and validation is valuable, the primary focus is on building the technical data infrastructure

that makes large-scale, automated validation possible.

You have a strong background in Data Engineering and enjoy solving challenges involving large datasets, distributed processing,

and scalable data architectures.

You understand that good data engineering is about more than moving data — it is about building reliable foundations that make

data useful, traceable, and trustworthy.

You enjoy working with complex systems, taking ownership of technical challenges, and collaborating with others to improve how

data is processed and used.