AI Data Architect – Scalable Enterprise Data Solutions

About the role

The AI Data Architect will join BASF's Digital Hub in Madrid to design and implement enterprise‑grade data architectures that power AI and automation solutions. You will work in a project‑oriented team, ensuring data platforms are scalable, reliable, and aligned with business value.

Key responsibilities

• Define and own end‑to‑end data architecture for AI solutions, covering ingestion, storage, and serving layers such as batch pipelines and real‑time APIs.
• Design data foundations for compound AI systems, including retrieval‑augmented generation (RAG), vector and knowledge stores, and feature/embedding layers.
• Establish data‑modeling standards, semantic layers, and reusable reference architectures across batch, streaming, analytical, and AI‑driven workloads.
• Define and enforce governance frameworks for data quality, lineage, security, and compliance.
• Set architectural guidelines and best practices for scalable data platforms and ensure consistent adoption.
• Provide technical leadership to data engineers, data scientists, and business partners.
• Evaluate emerging technologies and shape the strategic roadmap for the data and AI platform.

Required profile

• Bachelor’s or Master’s degree in Computer Science, Information Systems, or a related field.
• At least 5 years of experience in data engineering and data architecture, including designing enterprise data solutions.
• Proven ability to lead cross‑functional teams and drive data‑centric projects.

Required skills

• Data architecture and data engineering
• Batch processing pipelines
• Real‑time APIs
• Retrieval‑augmented generation (RAG)
• Vector stores and knowledge stores
• Feature and embedding layer design
• Semantic data modeling
• Data governance, quality, lineage, security, and compliance

What we offer

• Opportunity to shape AI‑driven data platforms at a global chemical leader.
• Collaborative environment within BASF Digital Hub Madrid.
• Access to cutting‑edge technologies and continuous learning.