To expand our Data DevOps Team and to help drive our business we are looking for a:

EXPERIENCE:

Must

• Software engineer education or by training
• 5+ years of software development and cloud experience
• Pandas/polars
• Python, R, Bash
• Linux and Docker usage
• DevOps mindset

Nice to have

• Shiny, DJANGO, FastApi, Pandas/polars, Pydantic
• Unit testing
• Gitlab CI/CD
• Familiar with AWS EC2, AWS S3
• Rust

You are someone who:

• Is a good communicator, as you will work with different stakeholders.
• Can organize your own work and manage expectations.
• Enjoys working in a flat organization with minimal hierarchy.

As an experienced software engineer, you will work with the data science, bioinformatics and breeding team to turn the latest research insights into production-ready code. Writing reliable code that excels in speed and maintainability is your strength. Naturally proactive, you improve the technology stack with new software packages and promote good software development practices. Embracing a DevOps way of working, you are both result-driven and empathetic, always seeking to grow as a team. You enjoy working on the AWS cloud environment or are at least keen to get familiar with AWS cloud services.
Typical project 1: drones
The agronomy research team discovers a new methodology to monitor potato plants, based on analysis of drone imagery from daily flights. Together with the data science team, you develop processing code, and a Shiny dashboard to visualize the results. With the data engineer you setup datasets in the data lake, and schedule daily processing pipelines. With the DevOps engineer, you deploy your code and dashboard to AWS ECS. Due to your work, field trials are more effective, and additional stress resistant potato varieties are available much quicker.
Typical project 2: selection model
The breeding team proposes a new genomic prediction model for plant selection. Together with the breeding and bioinformatics teams, you help to write production-ready code from the start, ensuring high quality and maintainability. You ensure that the model is tested and can be monitored, so that breeders have in-depth feedback on their model. Because of your interest in science, you pick up some domain knowledge along the way, making you an effective sparring partner for your colleagues.