AI Data Architect

Define and own the end-to-end data architecture for AI solutions, from ingestion and storage to serving layers powering models and analytics (e.g., batch pipelines, real-time APIs).

• Design the data foundations for compound AI systems, including retrieval architectures (e.g. RAG), vector and knowledge stores, and feature/embedding layers.
• Establish data modelling standards, semantic layers, and reusable reference architectures across workloads (batch, streaming, real-time, analytical, AI-driven) across the organization.
• Define and enforce governance frameworks for data quality, lineage, security, and compliance, ensuring trustworthy and well-managed data products.
• Set architectural guidelines and best practices for scalable data platforms and pipelines, and ensure their consistent adoption
• Provide technical leadership and guidance to data engineers, data scientists, and business partners on data and AI architecture.
• Evaluate emerging technologies and define the strategic roadmap for the data and AI platform.

• Stay current with trends and best practices in data architecture, AI, and cloud platforms., Because we are counting on innovative solutions, sustainable actions, connected thinking and on you, become a part of our formula for success and develop the future with us - in a global team that embraces diversity and equal opportunities irrespective of gender, age, origin, sexual orientation, disability or belief. At BASF, we are committed to upholding and ensuring compliance with company standards related to quality, environment, health, safety, and energy, in line with our global guidelines. We actively promote a culture of prevention and continuous improvement, encouraging collaboration in initiatives related to quality, environmental protection, health, safety, and energy performance. We foster responsible energy use, promoting efficiency in daily operations and supporting the identification of improvement projects and energy-saving opportunities., Nunca debes compartir tus datos bancarios ni fotos de tus documentos al solicitar un empleo. Si tienes alguna duda sobre un proceso de selección En esta oferta serás redirigido a la pagina web de la empresa. Completa el formulario en su web.

• Madrid - España Ubicación

• Arquitecto TIC Funciones

• Jornada completa Jornada

• Más de 5 años Experiencia

• Indefinido Tipo contrato *

Bachelor´s degree or Master´s in computer science, Information Systems, or a related field.

• 5+ years of experience in data engineering and data architecture, including designing data models, platforms, and end-to-end data pipelines. Proven experience defining data architecture for AI/analytics solutions on a major cloud platform (Azure preferred; AWS a plus) and Big Data architectures.
• Data architecture and modelling for relational and NoSQL systems, including modern storage paradigms (e.g., object storage, lakehouse, warehouse).
• Design of scalable data platforms and architectural patterns (e.g., Lakehouse, Data Mesh, Medallion), including governance, lineage, and quality considerations.
• Architecture of compound AI systems, including data layers for AI solutions (e.g., RAG, GraphRAG), vector stores, graph databases, and embedding pipelines.
• Strong programming skills in Python, including asynchronous programming (asyncio) and data processing.
• Apache Spark and Databricks platform
• Cloud data platform expertise, preferably Azure Could and Azure data platform services.
• Streaming and event-driven architectures, using streaming services such as RabbitMQ or Apache Kafka
• Big data and large-scale compute architectures, including batch and real-time processing patterns.
• Design of microservices and distributed systems, including API-based data services.
• Containerization and deployment practices using Docker (and Kubernetes as a plus)
• Data security, privacy, and compliance (e.g., GDPR), including encryption, access control, and data masking/anonymization
• Software engineering practices, including Agile methodologies (Scrum, Kanban) and DevOps (CI/CD with GitHub Actions)
• Container orchestration platforms: Kubernetes
• Graph database technologies and data modelling
• Workflow orchestration and task management frameworks such as Apache Airflow and Celery
• AI/ML platforms and cloud AI services
• LLM and agentic solution patterns, including prompt engineering and orchestration of AI agents.
• MLOps practices, including model lifecycle management, CI/CD for ML, deployment, monitoring, and retraining pipelines.
• Strong problem-solving skills with the ability to work both independently and collaboratively in cross-functional teams.
• Excellent communication and stakeholder-management skills, with the ability to translate business needs into technical architectures and influence decision-making across teams.

A secure work environment because your health, safety and wellbeing is always our top priority.

• Flexible work schedule and Home-office options, so that you can balance your working life and private life.
• Learning and development opportunities
• 25 holiday days per year
• 5 additional days (readjustment)
• A collaborative, trustful and innovative work environment
• Being part of an international team and work in global projects
• Relocation assistance to Madrid provided

At BASF, the chemistry is right

Digital Hub Madrid attracts, grows, and develops passionate people who will meaningfully impact the digital future of BASF. Come join us and be a part of our digitalization journey.

Describe your Product Mission here / objective of the role: The AI & Automation Enablement team designs and engineers scalable AI and automation solutions that deliver measurable business value. By combining strong architecture, engineering excellence, and industrialization capabilities, we enable BASF to turn opportunities into production-ready systems - consistently, reliably, and at scale.

About the Job: AI Data Architect in a project-oriented team who designs scalable, enterprise-grade data architectures and leads the engineering of robust data platforms, collaborating across domains and teams to enable the development and industrialization of AI solutions that deliver measurable business value.