【Alexion Japan】Snowflake Data Platform

Role Overview • The Principal Data Architect – APJ Snowflake Data Platform will provide technical architecture leadership for the design, evolution, and governance of the APJ enterprise data platform. • This role will define the target architecture and technical standards for a scalable, secure, and governed data ecosystem centered on Snowflake , supporting enterprise data engineering, business intelligence, advanced analytics, and AI use cases across APJ. • The Principal Data Architect will work closely with Data Engineers, BI and Analytics teams, business stakeholders, and global technology teams to translate business and data requirements into sustainable enterprise architecture. • This is not only an advisory architecture role. The successful candidate is expected to have deep hands-on Snowflake expertise and be able to review technical designs, challenge engineering decisions, troubleshoot complex issues, and provide practical architectural guidance. Key Responsibilities 1. Snowflake Platform Architecture • Define and evolve the target architecture for the APJ Snowflake data platform. • Design scalable architecture patterns for enterprise data ingestion, transformation, storage, consumption, and analytics. • Establish architectural principles for database, schema, warehouse, and data-layer design. • Define architecture supporting BI, Advanced Analytics, Data Science, and AI workloads. • Ensure architecture decisions balance scalability, performance, security, maintainability, and cost. 2. Enterprise Data Architecture • Define common architectural patterns for integrating major enterprise data domains. • Establish data-layer and data-modeling principles across source, transformation, and consumption layers. • Define reusable architectural patterns that can be adopted across APJ markets. • Guide the design of trusted and reusable enterprise data products. • Ensure local market requirements can be accommodated without unnecessary architectural fragmentation. 3. Snowflake Security & Access Architecture • Define Snowflake security and access-control architecture. • Establish principles for role-based access control and appropriate separation of responsibilities. • Partner with Security and Identity teams on enterprise access requirements. • Provide architecture guidance for secure handling of sensitive commercial and customer data. • Snowflake role design and security-related approvals are already among the architecture topics documented internally. 4. Data Integration & Transformation Architecture • Define architectural standards for data ingestion and transformation using Fivetran and dbt . • Establish patterns for source-to-Snowflake integration. • Define scalable approaches for ELT and transformation architecture. • Guide engineering teams on reusable dbt models and data-layer design. • Review pipeline and transformation designs for architectural consistency. 5. Architecture Governance & Design Authority • Serve as a technical design authority for major APJ data platform initiatives. • Lead architecture and solution design reviews. • Review technical proposals and identify architecture risks, dependencies, and technical debt. • Define and maintain architecture standards, principles, and reusable patterns. • Ensure new data solutions align with the APJ target architecture. • Partner with engineering teams to move from architecture design to practical implementation. 6. Platform Resilience & Operational Architecture • Define architectural principles for platform resilience, data protection, and recoverability. • Partner with relevant technology teams on business continuity and disaster recovery requirements. • Identify architectural risks and recommend improvements to platform resilience. • Disaster Recovery for Snowflake has also been an active internal architecture topic. 7. AI-Ready Data Architecture • Define a data architecture capable of supporting AI/ML and Generative AI workloads. • Establish architectural patterns for governed consumption of enterprise data by AI applications. • Work with Data Science and AI teams to ensure the underlying data platform supports emerging AI requirements. • Evaluate how Snowflake capabilities can be incorporated into the broader APJ data and AI architecture. • Internal discussions also reference the use of Snowflake for AI-related development and scaling data capabilities. Required Qualifications Snowflake Expertise • Deep hands-on experience with Snowflake is mandatory , including: • Enterprise Snowflake architecture and solution design • Data warehouse and analytical data architecture • Snowflake security and access architecture • Advanced SQL • Data modeling • Performance and scalability considerations • Production troubleshooting • Data integration architecture Data Engineering & Architecture Strong knowledge and practical experience in: • dbt • Fivetran • Modern ELT/ETL architecture • Enterprise Data Warehousing • Data Modeling • Data Integration • Data Quality • Data Governance • Git-based development and CI/CD concepts • Cloud data architecture • The candidate should be technically strong enough to challenge and guide Principal/Senior Data Engineers , rather than functioning only as a high-level solution architect. Language Requirements Japanese • Business-level proficiency required • The candidate must be able to independently: • Conduct architecture discussions with Japanese stakeholders. • Translate business requirements into technical architecture. • Explain complex technical decisions to both technical and non-technical audiences. English • Business-level proficiency required • The candidate must be able to collaborate effectively with APJ and global technology, architecture, security, and data teams. Preferred Qualifications • Pharmaceutical or Life Sciences industry experience • Experience architecting large-scale enterprise Snowflake platforms • Experience with pharmaceutical commercial and custom