OverviewAs 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.
ResponsabilidadesBuild 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 principalesStrong 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 (España)
🏢 Agilent Technologies
📍 España