OVERVIEW

Physical AI, a real model of the world, is the next trillion dollar opportunity and a foundational pillar for energy, robotics and

superintelligence.

At Jua we are building it now. Our models already run on four continents and help power the energy buildout needed to support ever

larger intelligence.

We are assembling a world-class team of researchers and entrepreneurial minds to turn this model into reality at global scale. If

you want the opportunity of your life, come build physical AI with us.

WHAT WE’RE LOOKING FOR

We’re looking for an exceptional and ambitious Data Engineering Intern who’s eager to learn fast, take ownership, and contribute

to real production systems.

You’ll work together with our experienced data and AI engineers and support expanding and refining Jua’s data infrastructure,

focusing on data acquisition, validation, and integration using Dagster, Python, and modern cloud technologies. Your work will

directly accelerate our ability to onboard new datasets and improve model performance.

Internship duration: 3 months (extendable to 6 months)

RESPONSIBILITIES AND TASKS

Integrate and onboard new weather, climate, and geospatial datasets into Jua’s data infrastructure

Build and maintain robust data pipelines using Dagster, ensuring reliability and scalability

Collaborate with engineers and scientists to validate data quality, completeness, and usability

Contribute to documentation and automation that improve data ingestion and processing workflows

Support hindcast generation and other foundational data operations to increase engineering throughput

Learn directly from experienced mentors while contributing to production-grade systems that power Jua’s AI models

NEED-TO-HAVE

Currently pursuing or recently completed a Bachelor’s or Master’s degree in Computational Science, Engineering, Physics,

Atmospheric or Earth Science

or a proof that you are exceptional in your field without a degree (show us your projects on Github)

Strong programming skills in Python and familiarity with Git

High intellect, curiosity, strong attention to detail, and a drive to excel in a fast-paced environment where intensity, long

hours, and high standards are the norm

NICE-TO-HAVE

Understanding of data pipelines, ETL processes, and workflow orchestration tools such as Dagster, Airflow, or Prefect

Basic familiarity with GCP or AWS, and experience handling structured or geospatial data

Familiarity with Docker or containerized development

Knowledge of SQL and basic data modeling concepts

Interest in machine learning or large-scale simulation systems

AT THE END OF YOUR INTERNSHIP, YOU WILL HAVE

Built and deployed data pipelines used in production at Jua

Onboarded new datasets that enhance model accuracy and experimentation speed

Gained hands-on experience with Dagster, cloud infrastructure, and collaborative data workflows

Contributed directly to Jua’s mission to redefine how the world forecasts and understands the physical world

Demonstrated exceptional ownership, technical skill, and impact

ABOUT YOU

You’re technically strong, curious, and eager to learn fast

You take initiative and enjoy solving open-ended problems

You thrive in an environment where expectations are high and feedback is direct

You’re excited by the idea of working with world-class engineers and scientists on real-world data challenges

Please note: We prioritise your answers to the application questions over your CV, so we encourage you to complete them as

thoughtfully and thoroughly as possible.

At Jua, we foster a performance culture and value people who embody our beliefs of service and adventure. We prioritize agility,

operating at the highest clock speed to adapt quickly to change.

We innovate on behalf of our users and leverage data supremacy to maintain our competitive edge. Through clear communication and

fact-based decision-making, we ensure alignment in our pursuit of excellence.

With these principles, we aim to create a customer-focused, value-centric organization that sets new standards in the industry. We

value the unique perspectives that each individual brings to the table and believe that embracing diverse backgrounds and

experiences enriches our collective journey towards growth and success.

Roll

Data Engineering Intern

Plats

Zürich

Publicerad

7 januari

Sista ansökningsdag

16 augusti

Taggar för det här jobbet

Python AWS GCP Docker SQL AI Machine Learning

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