Head of Data Engineering – AI CoE

🔥 0 minutes ago

🌐 United States, Spain – Remote

🇺🇸 United States – Remote 🇪🇸 Spain – Remote

🏄 California – Remote

🏄 California – Remote

💵 $171.6k - $321.8k / year

⏰ Full Time

🔴 Lead

🚰 Data Engineer

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Agilent Technologies

WebsiteLinkedInAll Job Openings

10,000+ employees

Founded 1999

🍽️ Food & Beverage

🏥 Healthcare

💼 Consulting

💰 $500M Post-IPO Debt on 2019-09

Food & Beverage • Healthcare • Consulting

Agilent Technologies is a global leader in the field of analytical and laboratory instruments. The company offers a diverse range of products and solutions, including gas and liquid chromatography, mass spectrometry, lab supplies, and software and informatics. Agilent serves various industries, such as biopharma, food and beverage testing, clinical diagnostics, and environmental testing. Additionally, Agilent provides comprehensive services for lab management, maintenance, and instrument repair. They focus heavily on advancing science through sustainable solutions and supporting genomics, pathology, and cancer research with advanced technologies.

📋 Description

• Own the Fabric data plane containing certified data and semantics used by agents and BI use cases • Ensure certified data products include semantic definitions, data contracts, policy and entitlement metadata, agent identity, lineage, observability, and certification tiers • Deploy agents that generate metadata, resolve entities across domains, score quality, and classify unstructured content • Own certified, versioned data products and semantic models in partnership with domain owners and stewards • Oversee the Asset Registry, lineage, and data-quality signals • Develop lakehouse, vector, and graph retrieval foundations for grounded agent behavior • Manage AI Data Engineers deployed into pods • Lead the design, development, and implementation of modular data models, data pipelines, and data management frameworks • Define data engineering priorities and direct scalable data solution development • Establish standards and processes for data reliability, efficiency, quality, compatibility, and accessibility • Provide technical and organizational leadership for data platforms and tools supporting analytics, data science, predictive and prescriptive modeling, and automation • Oversee project execution, cross-functional collaboration, talent development, and continuous improvement of data engineering capabilities

🎯 Requirements

• Bachelor’s or Master’s Degree or equivalent • Broad knowledge of relevant functional area(s) • Minimum of 10 years’ experience formally or informally leading people, projects and/or programs • Track record building enterprise data platforms serving production AI systems, not only analytics • Experience with semantic layers, ontologies, or knowledge representation at scale • Deep familiarity with modern lakehouse, vector, and graph technologies • Experience with Microsoft Fabric, Snowflake, or equivalent platforms in a multi-cloud estate • Experience operating data contracts, lineage, and certification models in a regulated or quality-driven industry • Life sciences or GxP exposure is a strong plus • Curiosity about AI, including its potential and pitfalls • Lifelong learning and deliberate toolkit reinvention • Excellent communication and ability to influence • Ability to adapt communication from bench scientist to Board level • Preference for automating curation with AI rather than scaling it with headcount

🏖️ Benefits

• Eligibility for bonus • Stock • Benefits • Pay and benefit information by country available through Agilent's locations information • Equal employment opportunity and inclusive workplace • Disability assistance during the application or interview process