Senior Data Engineer

Posted Yesterday
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Zürich
Senior level
Artificial Intelligence • Software
The Role
Develop and improve scalable ETL pipelines in the cloud, process various data types, enhance a data warehouse for weather modeling, and ensure performance and high availability. Collaborate in an agile environment and test new approaches while handling large data volumes.
Summary Generated by Built In
Overview

Jua's mission is to create artificial general intelligence (AGI). Our product uses a foundational Earth systems model to predict atmospheric events. It’s more accurate, faster, and updates more frequently than current weather models, making it valuable for traders in weather-dependent power markets. These benefits are crucial during extreme weather events like hurricanes and cyclones. As we scale the model, more applications will become possible, including wildfire, flood, and vegetation prediction.
By joining our talented multidisciplinary team, you'll help shape our culture of ambition, transparent communication, and rapid iteration. We offer exciting challenges, creative freedom, fair pay, and generous stock options.

Responsibilities and tasks

  • Developing and improving scalable ETL pipelines in the cloud

  • Loading, processing, normalizing and providing various data types, from point data such as sensor measurements to raster data such as satellite or radar

  • Developing and improving an extensible data warehouse as the heart for weather modeling

  • Ensuring Performance, robustness and high availability

  • Development of interfaces for the exchange of data from a wide variety of applications

  • Testing, validating, visualizing and documenting new approaches and their performance

Need-to-have

  • Hold a senior position at a reputable company or at least 5 years of professional experience in the field of data engineering 

  • Experience in data heavy environments 

    • Experience in handling large amounts of data (>1TB)
  • You have already set up scalable ETL pipelines, know the common database systems and have experience with common ETL libraries

  • Experience with distributed systems and various cloud providers

  • You are proficient in Python, as well as at least one other modern/mainstream programming language (C/C++, Java, Julia or Go)

  • You can develop solutions independently based on targets and have experience with agile work 

  • You have experience and interest in the development of the idea, from a prototype to the finished product

  • You appreciate the values of an open feedback culture and transparency

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.

Top Skills

C
C++
Go
Java
Julia
Python
The Company
HQ: Schwyz
42 Employees
On-site Workplace
Year Founded: 2022

What We Do

Jua.ai - Accuracy beyond expectation. Use beyond belief. The world's first end to end deep learning model for weather forecasting, delivered on an intuitive platform for anyone to customise it. Startups, governments and large companies alike can now develop global, high frequency and high accuracy weather models within days.

Jua’s mission is focused on achieving artificial general intelligence (AGI) through a deep exploration of physics, the universe, and their interaction with the human civilisation. We are initially building the world's largest AI weather forecasting model so far and - to our knowledge - the first truly end to end one. This will help energy companies deal with weather volatility by way of significantly better and faster prediction as well as much more flexible extrapolation of insights.

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