Senior AI Data Engineer, Data Products & RAG Foundations
Agilent Technologies24 days ago
Barcelona, SpainSenior
Responsibilities
- Build and maintain governed, reusable AI-ready data products and pipelines with lineage, metadata, access controls, documentation, and certification requirements.
- Establish data quality standards, quality scoring, and model-readiness criteria for reliable AI behavior and business outcomes.
- Partner with data owners, stewards, subject matter experts, business stakeholders, Legal, Quality, Security, and IT teams to define authoritative sources and trusted domain models.
- Design retrieval foundations for structured and unstructured data, including chunking, embeddings, hybrid retrieval, vector search, graph-based approaches, and semantic enrichment.
- Apply AI-assisted metadata generation, entity resolution, and content classification to improve data quality, scalability, and discoverability.
- Design and implement scalable ingestion, integration, and storage frameworks across cloud and on-premises environments.
- Create reusable data assets, tools, services, patterns, and documentation for AI engineers, data scientists, analytics teams, and future use cases.
Requirements
- Strong data engineering experience building AI-ready data products rather than only warehouse tables and dashboards.
- Hands-on familiarity with Microsoft Fabric, Snowflake, vector databases, graph stores, data contracts, lineage, and certification requirements.
- Experience with RAG foundations, including chunking, embedding, hybrid retrieval, and understanding retrieval quality’s impact on AI behavior and outcomes.
- Ability to work within a business domain, understand data meaning, and build assets for reuse across multiple consumers and use cases.
- Excellent communication and influence skills with technical and non-technical audiences.
- Curiosity about AI, its limitations and emerging approaches, with a focus on responsible implementation and continuous learning.
- Bachelor’s or master’s degree in Computer Science, Engineering, Information Systems, Data Science, or a related field, or equivalent practical experience.
- Typically at least 8+ years of relevant experience.
Benefits
- Full-time role with a day shift and no stated end date.
- Travel required 10% of the time.
- Pay and benefit information varies by country and location; specific pay ranges are available through the hiring process.
Tech Stack
Snowflake
Categories
Data Engineering
About Agilent Technologies
Agilent Technologies builds analytical instruments, lab software, diagnostic and genomics solutions, plus consumables and services used by pharmaceutical, chemical, environmental, and clinical labs. It sells systems such as chromatography and mass spectrometry platforms, pathology and molecular diagnostic kits, and supports lab operations through its CrossLab services business. Founded in 1999 and headquartered in Santa Clara, California, Agilent is a public company listed on the NYSE (ticker: A) with global manufacturing and R&D sites.