13 set - Milano
Eurofins BioPharma Product Testing Italy
pbCompany Description /b /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/ppbAbout the role /b /ppWe are transforming laboratory operations into a fully digital, data-driven and increasingly intelligent laboratory environment. /ppAs a bData Engineering Intern /b – 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/ppbWhat you will work on /b /ppb1. Laboratory Data Engineering /b /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 /ulpb2. Laboratory Systems Data /b /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 /ulpb3. Power BI Analytics Automation /b /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 /ulpb4. Data Integration APIs /b /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 /ulpb5. AI Machine Learning Exposure /b /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 /ulpb6. Digital Laboratory Automation /b /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/ppbWhat we are looking for: /b /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 /ulpNice to have: /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/ppbYou do not need to know all of these technologies. Strong Python/SQL fundamentals and the ability to learn are more important. /b /ppbr/ppbAdditional Information /b /pulliLocation: Vimodrone (hybrid – 2 days remote/week) /liliDuration: 6 months internship /liliFlexible working hours /liliSalary: 1000€/month + €8 buoni pasto/day /li /ulpbr/ppThis is a b6-month internship role /b with bno guaranteed extension /b, but strong performers may be considered for extension or full-time opportunities. /p
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