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Data Engineer Internship (m/f/x)

External
Procter & Gamble logoProcter & Gamble · Madrid General Office
Full-timeOn-site3d ago
AgileAzureCI/CDCore DataData ModelingGit
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Responsibilities

  • Design and build scalable Data & Analytics solutions in Microsoft Azure to obtain, process, store, and serve trusted data.
  • Develop data pipelines and data environments within existing Azure solution designs to generate valuable business insights.
  • Support automation and optimization of internal data processes to improve quality, speed, and reliability.
  • Collaborate with multifunctional and multinational teams across P&G to deliver business-focused outcomes.
  • Contribute code in Python and SQL, following engineering best practices and clean coding standards.
  • Use Git/GitHub and CI/CD practices to manage changes and support team delivery workflows.
  • Learn and grow through mentorship while contributing to analytics and AI-enabled use cases under guidance.

Requirements

  • Understanding of Spark framework and distributed architecture features and challenges.
  • Experience implementing projects with Microsoft Azure stack such as Databricks, Azure Data Factory, Azure Analysis Services, SQL Server, or Azure Synapse.
  • Knowledge of Agile and DevOps methodologies.
  • Exposure to machine learning concepts or frameworks such as PyTorch or TensorFlow.
  • Job Schedule
  • Full time
  • Job Number
  • R000153580
  • Job Segmentation
  • Internships
  • Starting Pay / Salary Range
  • €1.200,00 / month

Benefits

Responsibility from Day 1 - Contribute to real data engineering work that supports business decisions and analytics solutions from the start.Development Opportunities - Build hands-on experience in modern cloud data engineering, Azure components, Python, SQL, Git/GitHub, and CI/CD practices.Meaningful Work - Help strengthen trusted data foundations in a diverse, flexible, and business-driven environment.Coaching and Mentorship - Receive ongoing guidance from experienced engineers while learning how to deliver resilient, high-quality solutions.Collaborative Environment - Work with multifunctional and multinational teams that value engineering excellence, curiosity, and innovation.Join UsApply by clicking on the button below. To learn more about the P&G recruitment process, please visit this link: Hiring Process .Job QualificationsCurrent enrollment in, or recent completion of, a Bachelor's or Master's program in Computer Science, Mathematics, Software Engineering, or another relevant engineering field.Business understanding and strong interest in translating business questions into data and analytics solutions that create measurable impact.Strong foundational programming skills in Python and SQL.Foundational understanding of cloud technologies, preferably Microsoft Azure.Understanding of data modeling and core data engineering concepts.Understanding of CI/CD principles and version control using Git/GitHub.Effective communication skills in English and a proactive teamwork approach.A curiosity-driven mindset with a commitment to learning, quality, and impactful results.Flexible schedule

Additional Information

Job Location MADRID GENERAL OFFICE Job Description Are you passionate about building scalable data solutions that turn complex business challenges into trusted insights? Do you have a strong technical mindset, curiosity, and a desire to learn in a real multi-billion business environment? If so, consider joining P&G as a Data Engineer Intern in Madrid. This role is for individuals eager to shape the future of our data strategy by designing, developing, and improving modern data and analytics solutions. As a Data Engineer Intern , you will contribute to end-to-end analytics applications that help enable high-quality, resilient, and business-relevant data delivery. You will work with modern Microsoft Azure components and tools, develop data pipelines and environments, and collaborate with multifunctional and multinational teams across P&G. With guidance from experienced engineers, you will help build trusted data foundations that support analytics, automation, and AI-enabled use cases.

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