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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data & AI Engineering Consultant - **Company:** Xomnia - **Location:** Amsterdam, Netherlands - **Experience:** Starter - **Salary:** €3,300.0 - **Contract:** Internship / Graduate position - **Skills:** Artificial Intelligence, Airflow, Amazon Web Services, Data Analysis, Microsoft Azure, Cloud Computing, Continuous Integration, Information Engineering, Data Infrastructure, Python (Programming Language), Machine Learning, Raw Data, Power BI, Cloud Services, SQL Databases, Snowflake, Git, Scikit Learn, Information Technology, Data Management, Machine Learning Operations, Docker - **Published:** August 8, 2026 - **Apply:** https://careers.xomnia.com/o/junior-data-ai-engineer ## About the Role o A completed Master's in Computer Science, Artificial Intelligence, Data Science, Econometrics, Mathematics, or a related technical field. You graduate in 2026 or graduated recently. o Solid programming skills in Python, and you can write SQL queries that hold up. o Experience in Git. o A foundation in statistics and mathematics, and an understanding of common machine learning algorithms. o Familiarity with cloud (Azure or AWS). Course projects, internships and side projects all count. o Curiosity about the business side. You want to know why a client needs something, not just what they asked for. o Communication skills. You can explain something technical to someone who is not technical. o Fluency in English and Dutch. o The drive to learn fast, ask for feedback and share what you know. You do not need to tick every box. If you are strong on the fundamentals and eager to build the rest, we want to talk to you. ## Description At Xomnia we use data and AI to solve problems that actually matter. From advancing cancer research and keeping the electricity grid stable, to detecting real-time fraud and helping The Ocean Cleanup get plastic out of the ocean. Our clients range from KLM and Rabobank to Enexis and ASML. As a graduate Data & AI Engineering Consultant you join that work directly. Not as an observer, but as part of a project team, with a senior colleague next to you and room to make mistakes while you learn. Our culture runs on curiosity, shared ownership and a willingness to challenge assumptions. We are challengers, we embrace agility, and we are always sharing. And yes, we have fun. Think Learning Labs, company trips, boat rides through the Amsterdam canals straight from our office, and a free healthy lunch every day. One role, three directions Every Data & AI Engineering Consultant at Xomnia works from the same foundation: strong engineering, sharp thinking, and the ability to explain both to a client. Where you apply that foundation depends on the team you join: o Data Platforms: You build the pipelines and cloud infrastructure that make everything else possible. Think Python, SQL, Airflow, Azure and AWS. o Analytics & Data Engineering: You turn raw data into models, dashboards and KPIs that businesses actually use to make decisions. Think dbt, Snowflake, Power BI and data modeling. o AI: You design and deploy models that go into production and stay there. Think scikit-learn, MLOps, Docker, CI/CD and GenAI. You do not pick one when you apply. We use the interviews to figure out where your skills and interests fit best, and we tell you what we see. If you already know exactly which direction you want, tell us, we will take that seriously. And it is not a life sentence either: our Career Pathway maps out how you grow from Junior to Medior to Senior, and people do move between specializations along the way., o Write clean, efficient and maintainable Python and SQL. o Build and maintain data pipelines under supervision, and gradually take on your own components. o Get hands-on with cloud services on Azure or AWS. o Turn analyses into something a client can act on, and present that clearly. o Ask the questions that get to the root of a problem instead of the symptom. o Join our Learning Labs, share what you pick up, and use feedback to get better fast. ## Related Videos - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [How a Small Team Shrank a Microsoft Monorepo by 94%](https://www.wearedevelopers.com/videos/1236-how-a-small-team-shrank-a-microsoft-monorepo-by-94) - [AI Model Management Life Circles: ML Ops For Generative AI Models From Research to Deployment](https://www.wearedevelopers.com/videos/1152-ai-model-management-life-circles-ml-ops-for-generative-ai-models-from-research-to-deployment) - [Docker build without Docker](https://www.wearedevelopers.com/videos/100114-docker-build-without-docker) - [Introduction to Azure Machine Learning](https://www.wearedevelopers.com/videos/368-introduction-to-azure-machine-learning) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it) - [The Most Popular IT Jobs on the Market](https://www.wearedevelopers.com/magazine/376-the-most-popular-it-jobs-on-the-market) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development)