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AstraZeneca

Global pharmaceutical company developing prescription medicines

IT Principal Architect - Data and AI Architect

Data ManagementConfirmed live in the last 24 hours
Full-timeChinaNo salary listedIn-person

About the Job

Requirements

  • A bachelor's degree or above in Computer Science, Data Science, or a related technical discipline.
  • Deep practical knowledge of modern enterprise data platform architecture, including platform component design, data modelling, data integration, data governance, and data product lifecycle.
  • Hands-on experience with mainstream data platform technologies, including data lakes, lakehouses, warehouses, data pipelines, catalogs, access control, and API-oriented data services.
  • Practical understanding of agentic AI and generative AI enablement scenarios running on enterprise data platforms.
  • Ability to assess global reference data platform capabilities, identify gaps, and design local adaptations for China-specific compliance and operational constraints.
  • Ability to lead architecture reviews for complex data platform initiatives and deliver comprehensive architecture documentation.
  • Eight years of data architecture or AI architecture experience; enterprise data product and governance experience is required.
  • Five or more years of enterprise-grade data platform and data architecture experience, with a proven track record in enterprise data platform project delivery, data governance, and reusable data product delivery.
  • Strong awareness of China data security, personal information protection, and data residency regulatory requirements.
  • Excellent cross-region collaboration to align requirements with global data platform teams.

Responsibilities

  • Define governed enterprise data-platform architecture, platform capability blueprints, reusable data products, data integration patterns, and agentic-AI enablement patterns built upon China data platforms.
  • Establish local data-platform architecture standards, platform component selection guidelines, data governance principles, and operational guardrails, balancing the global enterprise framework with China regulatory constraints.
  • Produce data-platform architecture diagrams, platform component specifications, data-product definitions, and architecture decision records for local and global stakeholders.
  • Define end-to-end architectures for enterprise AI solutions, including model access, retrieval-augmented generation, agent orchestration, tool integration, and connections to enterprise applications and governed data services.
  • Establish architecture patterns and guardrails for AI evaluation, deployment, versioning, and monitoring, addressing output quality, security, privacy, access control, and human oversight in collaboration with governance teams.
  • Define architecture patterns for model training, fine-tuning, and inference, including training data preparation, experiment tracking, model evaluation, deployment, and lifecycle management, in collaboration with data science and machine learning engineering teams.
  • Guide and validate AI solution optimization across model selection, prompt design, retrieval quality, agent workflows, and model fine-tuning where appropriate, balancing business outcomes, accuracy, reliability, latency, and cost.
  • Drive alignment of China's local data platform with global enterprise data-AI reference platforms; design and document justified local adaptations for China-specific data regulation, residency requirements, and business needs.
  • Participate in enterprise architecture governance and lead architecture reviews for major China data-platform, data product, and AI-enabled projects.
  • Evaluate data-platform technical risks, platform capacity limits, technical debt, compliance gaps, and performance bottlenecks; propose platform modernization and improvement roadmaps.
  • Evaluate emerging data and AI technologies; design and conduct hands-on proofs of concept to validate feasibility, business value, architectural fit, and operational readiness, and recommend adoption based on defined success criteria.
  • Continuously assess and evolve existing data and AI platform architectures; drive agreed improvements in performance, resilience, scalability, observability, maintainability, and cost efficiency with engineering and operations teams.
  • Collaborate with global data-platform teams, local data engineering, platform operations, business, and delivery teams to guide end-to-end data-platform design, implementation, and lifecycle management.

Desired Qualifications

  • Multinational enterprise data platform architecture work experience.
  • Solid experience in end-to-end project delivery.
  • Hands-on project experience within the life science or pharmaceutical industry data domain.
  • Relevant data architecture or platform certifications.

About the Company

AstraZeneca

Global pharmaceutical company developing prescription medicines

AstraZeneca develops and markets prescription medicines and vaccines worldwide, with a focus on oncology, cardiovascular/metabolic, respiratory, and infectious diseases. Its products work by targeting specific biological pathways or cells, using small-molecule therapies, biologics, and vaccines to treat diseases or prevent infections. It differentiates itself through its dual heritage from Sweden and the UK, a broad pipeline, and strong R&D and collaborations that move from discovery to patient access. Its goal is to improve people’s health by discovering, developing, and delivering medicines and vaccines to patients worldwide.

Company size
10,001+
Company stage
IPO
Headquarters
Cambridge, United Kingdom
Founded
1913

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