Overview

As a Senior AI Data Engineer, you will lead data product development within an AI-focused pod, enabling governance, reuse, and scalable AI-ready data foundations. You collaborate with AI engineers, domain experts, and stakeholders to build pipelines, metadata, and retrieval-ready assets that power enterprise AI and scientific workflows. You’ll help shape the data foundation by contributing to governance, quality, and scalable data assets across on-premises and cloud environments. This role offers impact through building reusable data products that drive trusted AI outcomes.

Responsabilidades

- Build and maintain AI-ready data products and pipelines with governance, lineage, metadata, access controls, and documentation from day one
- Design data products for reuse as enterprise capabilities, not just point integrations
- Define data quality standards, quality scoring, and model-readiness criteria for reliable AI behavior
- Partner with data owners, stewards, stakeholders, and IT to establish trusted definitions and authoritative sources
- Design data retrieval foundations including vector search, grounding, and semantic enrichment
- Apply AI-assisted techniques (metadata generation, entity resolution, content classification) to improve data quality and discoverability
- Develop scalable ingestion, integration, and storage frameworks across cloud and on-premises




- Create reusable data assets and services to support AI engineers, data scientists, and analytics teams
- Contribute data products, patterns, and documentation to the broader enterprise ecosystem
- Ensure AI solutions are grounded in validated business meaning and data contracts
- Maintain documentation and governance artifacts from inception to deployment
- Drive reuse and automation to shorten data-to-build time

Requisitos principales
- Strong data engineering experience building AI-ready data products beyond basic warehousing
- Hands-on familiarity with Microsoft Fabric, Snowflake, vector databases, and graph stores
- Experience with RAG foundations, including chunking, embeddings, hybrid retrieval, and understanding retrieval impact on AI behavior
- Domain and product mindset with ability to work with data stewards and subject matter experts
- Excellent communication and the ability to influence both technical and non-technical audiences
- Curiosity and growth mindset with commitment to responsible AI implementation
- Bachelor’s or Master’s degree in a related field or equivalent practical experience
- 8+ years of relevant experience for this level

- Excellent communication
- Influence and collaboration
- Curiosity and growth mindset
- AI-ready data products
- Data governance and lineage
- Metadata management

📌 Senior AI Data Engineer, Data Products & RAG Foundations - barcelona
🏢 Agilent Technologies
📍 Barcelona