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  • Principal Technology Architect (App, Data & AI)
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    Principal Technology Architect (App, Data & AI)
    3 days ago
    £90000–£110000 yearly
    Full-time
    London

    Job title: Principal Technology Architect (App, Data & AI) Department: 5D Enterprise Assessment Job type: Permanent Salary – 90 – 110 K Overview: As the Principal Data & AI Architect, you are the chief expert and domain owner for Stream 3: Data, Integration & AI. You will be our senior-most authority on how to turn a client's data from a chaotic liability into a strategic asset. You will own the entire data strategy, from governance and quality to modern data platforms, integration patterns, and the creation of a pragmatic, high-ROI AI/ML Roadmap. Key Responsibilities: • Own Stream 3 (Data & AI): Lead the end-to-end execution of the S3 stream, from current-state maturity assessment to future-state data & AI architecture., • Data Strategy & Governance: Design the client's Enterprise Data Strategy, Data Governance Framework, Data Quality Framework, and MDM Strategy., • AI & ML Roadmap: Lead AI-readiness workshops to identify and prioritize high-value use cases. You will design the AI/ML Roadmap and the supporting MLOps Architecture., • Data & Integration Architecture: Design the target-state Data Architecture (e.g., data mesh, data lake house) and the Integration Architecture (e.g., API-led, event-driven) needed to support it., • "Think Laterally" (Collaboration):, • Partner with our Principal Business Architect (S1) to ensure your data strategy enables their new Target Operating Model., • Partner with our Enterprise Architect (S2) to define the integration patterns required to modernize their legacy applications/ERP. Qualifications: • Experience: 18+ years of hands-on experience in data architecture, data governance, and data science leadership., • Deep Specialization: You must be a true expert across the entire data lifecycle. You have built data governance programs from scratch, designed modern cloud data platforms, and have practical experience developing and deploying AI/ML models., • Framework Fluency: Expert-level knowledge of DAMA-DMBOK, modern data architecture patterns (e.g., Data Mesh, Lakehouse), and MLOps., • Certifications: Top-tier cloud data certifications (e.g., AWS, Azure) are highly valued. TOGAF certification is a nice-to-have to ensure architecture-wide fluency., • Pragmatic Visionary: You are not just a data scientist. You can "think laterally" to connect a specific AI use case back to a tangible business KPI and then design the end-to-end data pipeline and governance required to make it a reality.

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