We are transforming laboratory operations into a fully digital, data-driven and increasingly intelligent laboratory environment.
As a Data Engineering Intern – Digital Laboratory, you will work on real-world projects that connect laboratory systems, data platforms, analytics and automation.
Your main focus will be data engineering: extracting, transforming, integrating and structuring laboratory data so that it can be used for Power BI, automation, AI and future machine-learning applications.
You will work with technologies such as Python, SQL, APIs, cloud data platforms and Power BI, while gaining exposure to laboratory systems and digital transformation in a regulated Life Sciences environment.
This is an opportunity to work on projects designed to eliminate manual data handling, reduce paperwork and unnecessary system interactions, and make laboratory processes faster and more intelligent.
What you will work on
1. Laboratory Data Engineering
- Develop Python and SQL solutions for data extraction and transformation.
- Build and maintain data pipelines for laboratory and operational data.
- Transform raw data into structured, reusable datasets.
- Support the development of laboratory data lake/lakehouse capabilities.
- Automate recurring data preparation activities currently performed manually.
- Implement basic data-quality checks and validation rules.
- Help document data sources, structures and transformations.
2. Laboratory Systems Data
- Work with data originating from laboratory systems.
- Support extraction and analysis of data through appropriate, supported integration mechanisms.
- Analyze, and identify opportunities for standardization and reuse.
- Help create datasets that can be used for laboratory analytics and reporting.
- Work with laboratory application specialists to understand how laboratory data is generated and used.
- You do not need previous industry experience. We are looking for strong technical fundamentals and curiosity about laboratory technology.
3. Power BI & Analytics Automation
- Support automated Power BI datasets, create and improve dashboards and manage reporting pipelines.
- Build data transformations that eliminate manual Excel preparation.
- Help develop reusable data models for laboratory KPIs.
- Investigate data-quality issues affecting dashboards and reports.
- Improve reliability and automation of recurring reporting processes.
4. Data Integration & APIs
- Work with REST APIs and system integrations.
- Develop scripts and connectors to move data between systems.
- Investigate different approaches to integrating laboratory and enterprise applications.
- Help build reusable integration components rather than one-off data extracts.
5. AI & Machine Learning Exposure
Although data engineering is the primary focus, you will also be exposed to AI and ML projects.
You may contribute to:
- Preparing datasets for ML models.
- Data pipelines supporting AI applications.
- Anomaly detection and laboratory performance analytics.
- AI-agent and RAG-based solutions.
- Data preparation for predictive laboratory use cases.
- Experimenting with automation technologies.
- The objective is to understand how good data engineering enables useful AI, rather than simply experimenting with AI tools.
6. Digital Laboratory Automation
You will also help identify opportunities to remove unnecessary manual work.
For example:
- Manual Excel extraction → automated pipeline
- Repeated data entry → system integration
- Manual report preparation → automated Power BI
- Paper-based information flow → digital workflow
- Manual data investigation → AI-assisted analysis
- You will work with the team to turn these opportunities into practical solutions.
What we are looking for:
- Currently pursuing a Bachelor's or Master's degree or recently graduated in: Computer Science, Data Engineering, Software Engineering, Information Technology, Mathematics / Statistics, Engineering or a related field.
- Good understanding of Python.
- Good understanding of SQL and relational databases.
- Strong analytical and problem-solving skills.
- Interest in data engineering and technology.
- Willingness to learn new technologies independently.
- Good English communication skills.
Nice to have:
- Experience with Power BI.
- Experience with Azure or another cloud platform.
- Experience with data pipelines / ETL / ELT.
- Knowledge of REST APIs.
- Familiarity with Git/GitHub.
- Python libraries such as pandas.
- Basic understanding of data lakes/lakehouses.
- Basic knowledge of machine learning.
- Experience with Power Automate or RPA.
- Interest in AI, LLMs or AI agents.
- Previous experience with laboratory, healthcare or pharmaceutical data.
You do not need to know all of these technologies. Strong Python/SQL fundamentals and the ability to learn are more important.
- Location: Vimodrone (hybrid – 2 days remote/week)
- Duration: 6 months internship
- Flexible working hours
- Salary: 1000€/month + €8 ticket restaurant/day
This is a 6-month internship role with no guaranteed extension, but strong performers may be considered for extension or full-time opportunities.