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Descripción Del Puesto

About the Role

We’re looking for a Data Engineer Intern who actually likes data, but someone who’s curious — someone who wants to understand how data works, why it behaves the way it does, and how to make it useful.

You don’t need years of experience. We care more about:

  • your mindset
  • your curiosity
  • your willingness to learn

You’ll work on real data problems connected to drug development and healthcare, helping build and maintain data pipelines that support cutting-edge analytics and AI.

You’ll join a team that genuinely cares about AI and Generative AI — we experiment, we learn, and we teach others. Expect a hands-on, supportive, no-BS environment.

What You’ll Do

  • Help design and maintain data pipelines (ETL/ELT) moving data from different sources into data platforms
  • Work with structured and unstructured data, learning how to clean, transform, and model it
  • Support development of datasets used for analytics, reporting, and machine learning
  • Collaborate with Data Engineers, Data Scientists, and Analysts to understand real business use cases
  • Learn how to monitor data pipelines, debug issues, and improve data quality
  • Contribute to documentation and data-related processes
  • Get exposure to cloud platforms (AWS) and modern data tools like Databricks
  • Explore how Generative AI can be used in data workflows

Requisitos

What We’re Looking For

We’re not expecting you to tick every box — but you should have some foundation and strong motivation to grow.

Must-have basics

  • Student (or recent graduate) in IT, Data, Engineering, or similar field
  • Basic knowledge of Python and/or SQL
  • Understanding of how data works (tables, databases, APIs, etc.)
  • Interest in data engineering, analytics, or AI/GenAI
  • Ability to think critically and solve problems
  • Good communication skills and willingness to learn

Nice to have (but not required)

  • Exposure to: AWS (S3, Lambda, etc.), Databricks / Spark, ETL tools or pipelines
  • Experience with Git (even basic)
  • Curiosity around Generative AI tools (e.g., GitHub Copilot or similar)
  • Any personal projects, coursework, or internships in data

What You’ll Gain

  • Hands-on experience with real-world data systems used in healthcare & pharma
  • Mentorship from experienced Data Engineers and AI specialists
  • Practical knowledge of: Data pipelines and ETL/ELT, Cloud data platforms (AWS), Modern tooling (Databricks, Git, CI/CD basics)
  • Exposure to AI & Generative AI in production environments
  • Opportunity to grow into a full-time Data Engineer role

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