Data Engineer - Automation & AI

Job Title: AI & Data Engineer [Interim]

Location: (Hybrid) Rotterdam

Engagement: Full-time, 5 days a week

Contract duration: 3-6 months (possibe extension)

Start date: ASAP

Context

A large, international company in the engineering sector is scaling production-grade AI across the organization. The Data & AI Platform team is expanding delivery capacity and is looking for an interim Data & AI Engineer who can step in immediately, take ownership of AI use cases end-to-end, and accelerate adoption across business teams on an Azure + Databricks foundation.

This is a hands-on delivery role with high autonomy: you will build, ship, operate, and improve AI solutions in production—while introducing reusable components and pragmatic best practices that raise the bar across the platform.

What you’ll do

* Deliver AI use cases end-to-end: from ingestion and feature engineering to model/agent development and production rollout.

* Design and operate Databricks lakehouse pipelines (batch and streaming) using Spark/SQL/Delta Lake, including monitoring and data quality controls.

* Build AI solutions on the platform, including:

* RAG patterns (retrieval, chunking, embeddings, evaluation)

* tool-using agents and orchestration approaches

* prompt strategies and testing/guardrails

* (where relevant) custom ML models and supporting pipelines

* Productionize and run what you build: reliability, observability, cost control, and operational hygiene.

* Enable other teams by creating reusable components, templates, and delivery standards.

* Work with governance and compliance: align with AI governance requirements and ensure solutions are secure and auditable.

* Collaborate with stakeholders across IT and the business to translate needs into working solutions and clear delivery increments.

What success looks like (first weeks)

* Rapidly understand the current Azure/Databricks landscape and delivery priorities.

* Pick up 1–2 active use cases and move them toward production-quality standards.

* Strengthen delivery patterns (templates, evaluation approach, monitoring, data quality checks).

* Create momentum with visible working increments and pragmatic documentation.

Required experience

* Proven experience as a Data Engineer / Data & AI Engineer delivering solutions into production environments.

* Strong hands-on Databricks expertise: Spark/SQL, Delta Lake, Jobs/Workflows, performance tuning.

* Strong Python + SQL for data engineering and AI/ML workflows.

* Experience building data pipelines with quality checks and operational monitoring.

* Practical experience with LLM-based solutions (RAG and/or agents), including prompt strategies and evaluation approaches.

* Comfortable working independently in an interim context: you can own delivery, communicate clearly, and unblock yourself.

Nice to have

* Azure services exposure (e.g., Azure ML, Azure OpenAI, Key Vault, Functions, ADF).

* LLM toolkits (LangChain, Semantic Kernel), prompt evaluation frameworks, early LLMOps patterns.

* CI/CD (GitHub Actions) and Infrastructure-as-Code (Terraform).

* ML frameworks (PyTorch, TensorFlow, scikit-learn) where needed.

Why this assignment

* Immediate impact: deliver AI use cases into production on a modern Azure Databricks platform.

* High ownership and autonomy: a true interim role where delivery outcomes matter.

* Real-world relevance: projects tied to large-scale operations in a complex, safety- and compliance-aware environment.