Kayrros

Junior Data Engineer M/F (6-month internship)

28 October 2024
Apply Now
Deadline date:
£50000 - £100000 / year

Job Description

Passionate about Climate, Energy and AI? Join Kayrros, as a Junior Data Engineer M/F (6-month internship)


Kayrros is a global climate technology company and the world leader in environmental intelligence.

Founded in 2016, it uses artificial intelligence and machine learning to analyze massive amounts of satellite imagery and other inputs at scale and generate standardized, near-realtime data on greenhouse gas emissions and energy supply chains used for trading, environmental compliance and reporting purposes, as well as bespoke data on emissions, climate risks, land-use change and other metrics used by public and private-sector actors such as asset managers, regulators, industrial and consumer-product companies, insurers and others in various proprietary applications. Kayrros technologies provide a powerful set of high-impact tools to reduce our climate footprint, manage climate risks, harden our resilience to extreme weather events, and accelerate the transition to a lower-carbon economy.

Kayrros’s accomplishments have earned it wide recognition. We have been named one of TIME‘s 100 Most Influential Companies, been featured on Fortune’s ‘Change the World’ list in both 2023 and 2024, named Top Five Company of the Year in Fast Company’s ‘World Changing Ideas’ 2024 awards, and won the Financial Times Tech Champion award.

We have offices in Paris, Houston, New York, London, Bangalore, and Singapore. Now, we’re looking to grow our outstanding team by hiring gifted individuals who want to disrupt global climate governance and shape the future of finance and the environment.

Join us to make a difference!

For more information, visit www.kayrros.com.

We are currently recruiting for our Paris office, a Junior Data Engineer M/F (6-month internship)


The Team

The Data Engineering Team is in charge of developing Kayrros’ key software components for remote sensing data processing as well as elaborating and running the pipelines that power Kayrros products.

The team has a specific focus on Earth observation data (optical, sar, lidar) and geolocation data.

As an example, the team has developed methane detection pipelines, deforestation pipelines, and many others.

What you will do

As a Data Engineer intern, you will:

  •  Work with remote sensing, geospatial and machine learning engineers to integrate and scale their algorithms,
  • Learn how to design, implement and operate large-scale imagery and data pipeline on Kubernetes,
  • Develop internal shared libraries to ease the creation and maintenance of data pipelines.

You will work with space-borne data sources used at Kayrros (optical, SAR, hyper-spectral).

Requirements

Ideal candidate

  • Eager to learn software development and data engineering.
  • Basics of Python, SQL, Kubernetes and Docker.
  • Curious about remote sensing data, like Sentinel-1, Sentinel-2, etc.
  • Can communicate clearly in English.

We encourage all qualified candidates, eager to learn and grow, to apply, even if they do not meet all of the requirements listed above.

Why join Kayrros?

This is an ideal opportunity if you are looking for a six-month internship starting in between January and May 2025 and you want to join a fast-growing start-up.

  • We are a young, fast-growing tech company and are extremely passionate about what we do.
  • We are located in the WeWork building on Rue la Fayette, 75009 (free drinks, events and a vibrant atmosphere).
  • You will work with an international team and practice your English (or Chinese, German, Greek, Portuguese…) on a day to day basis.

At Kayrros, we are committed to fostering an inclusive and diverse workplace. We believe in equal opportunities for all applicants, regardless of gender. We actively promote gender equality in all aspects of our recruitment process and encourage applications from individuals of all genders. If you don’t meet all the listed skills or qualifications, we still encourage you to apply.