Data Engineering - Working Student (Wroclaw)

Description du poste:

Working Student is a long-term paid internship, that allows you to kickstart your fabulous journey in the IT world. As our Trainee you can have experience working in such areas that correspond to full-time jobs. The internship usually lasts from 6 to 24 months. We are open to flexible working hours so that you can reconcile working with us with your studies. #OpenToYou.
As a Working Student in Data Engineering, you will contribute to designing, building, and maintaining data pipelines and storage systems that support AI/ML workflows. You will work on practical tasks such as data preparation, pipeline development, and performance monitoring, gaining hands-on experience with modern data engineering tools and practices. This role offers an opportunity to learn and apply software development lifecycle (SDLC) principles in real-world AI/ML projects.
Location: Poland, Wroclaw

As part of our team, you will:
* Assist in building and maintaining data pipelines for batch, ETL, and real-time processing.
* Support optimization of data processing and storage systems
* Participate in data transformation, enrichment, and integration workflows
* Help monitor data quality, pipeline performance, and model metrics
* Contribute to technical documentation and testing activities
* Collaborate with team members to ensure data readiness for AI/ML models
* Learn and apply best practices in software engineering and DevOps

Profil requis du candidat:

Must-Have:
* Active student status at minimum one year
* Knowledge of Python programming
* Understanding of SQL and relational databases
* Familiarity with data analysis libraries (e.g., Pandas)
* Interest in data engineering principles and ETL processes
* Willingness to learn workflow orchestration tools (e.g., Airflow, Kubeflow).
* Ability to work independently on assigned tasks and communicate effectively
It would be nice if you also had:
* Exposure to AI/ML concepts and frameworks (e.g., scikit-learn, TensorFlow)
* Experience with version control (Git) and basic software engineering practices
* Familiarity with cloud platforms (AWS, Azure, GCP)
* Previous academic or project experience in data processing or analytics