pstrongCompany Description /strong /ppIn over 37 years, Eurofins has grown from a single laboratory in Nantes, France, with more than 65,000 employees in a decentralized and entrepreneurial network of over 950 laboratories in more than 1,000 companies across 59 countries.
Eurofins companies offer a portfolio of over 200,000 analytical methods to assess the safety, identity, composition, authenticity, origin, traceability, and purity of biological substances and products.
/ppbr / /ppstrongAbout the role /strong /ppWe are transforming laboratory operations into a fully digital, data-driven and increasingly intelligent laboratory environment.
/ppAs a strongData Engineering Intern /strong – Digital Laboratory, you will work on real-world projects that connect laboratory systems, data platforms, analytics and automation.
/ppYour 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.
/ppYou 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.
/ppThis 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.
/ppbr / /ppstrongWhat you will work on /strong /ppstrong1.
Laboratory Data Engineering /strong /pulliDevelop Python and SQL solutions for data extraction and transformation.
/liliBuild and maintain data pipelines for laboratory and operational data.
/liliTransform raw data into structured, reusable datasets.
/liliSupport the development of laboratory data lake/lakehouse capabilities.
/liliAutomate recurring data preparation activities currently performed manually.
/liliImplement basic data-quality checks and validation rules.
/liliHelp document data sources, structures and transformations.
/li /ulpstrong2.
Laboratory Systems Data /strong /pulliWork with data originating from laboratory systems.
/liliSupport extraction and analysis of data through appropriate,



supported integration mechanisms.
/liliAnalyze, and identify opportunities for standardization and reuse.
/liliHelp create datasets that can be used for laboratory analytics and reporting.
/liliWork with laboratory application specialists to understand how laboratory data is generated and used.
/liliYou do not need previous industry experience.
We are looking for strong technical fundamentals and curiosity about laboratory technology.
/li /ulpstrong3.
Power BI Analytics Automation /strong /pulliSupport automated Power BI datasets, create and improve dashboards and manage reporting pipelines.
/liliBuild data transformations that eliminate manual Excel preparation.
/liliHelp develop reusable data models for laboratory KPIs.
/liliInvestigate data-quality issues affecting dashboards and reports.
/liliImprove reliability and automation of recurring reporting processes.
/li /ulpstrong4.
Data Integration APIs /strong /pulliWork with REST APIs and system integrations.
/liliDevelop scripts and connectors to move data between systems.
/liliInvestigate different approaches to integrating laboratory and enterprise applications.
/liliHelp build reusable integration components rather than one-off data extracts.
/li /ulpstrong5.
AI Machine Learning Exposure /strong /ppAlthough data engineering is the primary focus, you will also be exposed to AI and ML projects.
/ppYou may contribute to: /pulliPreparing datasets for ML models.
/liliData pipelines supporting AI applications.
/liliAnomaly detection and laboratory performance analytics.
/liliAI-agent and RAG-based solutions.
/liliData preparation for predictive laboratory use cases.
/liliExperimenting with automation technologies.
/liliThe objective is to understand how good data engineering enables useful AI, rather than simply experimenting with AI tools.
/li /ulpstrong6.




Digital Laboratory Automation /strong /ppYou will also help identify opportunities to remove unnecessary manual work.
/ppFor example: /pulliManual Excel extraction ? automated pipeline /liliRepeated data entry ? system integration /liliManual report preparation ? automated Power BI /liliPaper-based information flow ? digital workflow /liliManual data investigation ? AI-assisted analysis /liliYou will work with the team to turn these opportunities into practical solutions.
/li /ulpbr / /ppstrongWhat we are looking for: /strong /pulliCurrently 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.
/liliGood understanding of Python.
/liliGood understanding of SQL and relational databases.
/liliStrong analytical and problem-solving skills.
/liliInterest in data engineering and technology.
/liliWillingness to learn new technologies independently.
/liliGood English communication skills.
/li /ulpuNice to have: /u /pulliExperience with Power BI.
/liliExperience with Azure or another cloud platform.
/liliExperience with data pipelines / ETL / ELT.
/liliKnowledge of REST APIs.
/liliFamiliarity with Git/GitHub.
/liliPython libraries such as pandas.
/liliBasic understanding of data lakes/lakehouses.
/liliBasic knowledge of machine learning.
/liliExperience with Power Automate or RPA.
/liliInterest in AI, LLMs or AI agents.
/liliPrevious experience with laboratory, healthcare or pharmaceutical data.
/li /ulpbr / /ppstronguYou do not need to know all of these technologies.
Strong Python/SQL fundamentals and the ability to learn are more important.
/u /strong /ppbr / /ppstrongAdditional Information /strong /pulliLocation: Vimodrone (hybrid – 2 days remote/week) /liliDuration: 6 months internship /liliFlexible working hours /liliSalary: ****€/month + €8 buoni pasto/day /li /ulpbr / /ppThis is a strong6-month internship role /strong with strongno guaranteed extension /strong, but strong performers may be considered for extension or full-time opportunities.
/p

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