Data Engineer

Livestock & Crop Storage Solutions
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Livestock & Crop Storage Solutions

Build the data platform behind the greenhouse of the future!
At Ridder, we're developing a next-generation climate control platform that helps growers make better decisions and optimize crop production. This is not an analytics role. You will build and own the data foundation that powers forecasting, automation, and data-driven climate control in greenhouses around the world.
You'll work at the intersection of software engineering, IoT, and data platforms. From sensor data and weather forecasts to model training datasets and system telemetry, you ensure the data is reliable, traceable, and ready for action.
As our Data Engineer, you will own the complete data lifecycle and help shape the architecture of our platform.
Design and operate scalable data pipelines and time-series data platforms.
Define data contracts, quality standards, and versioned schemas across the platform.
Enable data scientists and software engineers with trusted datasets and feature pipelines.
Help build and grow the data engineering capability within the team.
Run the models in production: scheduled training, batch inference, model registry, deployment and monitoring.
Orchestrate the platform's scheduled jobs — ingestion, validation, training data, model runs, evaluation

What makes this role different?
You won't be building dashboards or reporting solutions.
You will work on a technology platform where data quality directly impacts real-world outcomes. Every dataset, validation rule, and pipeline contributes to better climate control decisions for growers worldwide.
5+ years of experience building production-grade data platforms and pipelines.
Strong Python and SQL skills.
Experience with time-series, IoT, industrial, or other high-volume data environments.
Experience with cloud platforms, containers, CI/CD, and infrastructure as code.
A strong ownership mindset with a focus on reliability, quality, and continuous improvement.
Experience with a workflow orchestrator (Dagster, Airflow, Prefect or similar).
Experience operating ML models in production: training pipelines, registries, scheduled inference, monitoring.

Experience with weather, energy, industrial, or agricultural data.
Familiarity with real-time systems and operational technology environments.

Work on a unique challenge that combines technology, sustainability, and food production;
A gross monthly salary between €4.500,- to €6.000,-;
29 days of annual leave plus 8% holiday pay;
Influence key architectural decisions in a growing platform;
Real ownership and direct impact on the future of greenhouse technology.

Send us your CV and tell us about a data pipeline you've built that kept running when something upstream failed. What happened, how did you solve it, and what did you improve afterwards?
Interested in building the data backbone of tomorrow's greenhouse technology? We'd love to hear from you. For more details, don't hesitate to contact Joren de Bruijne via jobs@ridder.com.
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