Lead GCP Solution Architect

We are seeking an experienced and hands-on Lead GCP Cloud Solution Architect to lead the architecture, design and implementation of BMJ's next-generation Cloud Data Platform on Google Cloud Platform (GCP).

This is a highly hands-on architecture and engineering leadership role. The successful candidate will act as the technical authority for the Cloud Data Platform, responsible for defining the target-state architecture, engineering standards and best practices while actively contributing to the implementation of the platform.

You will architect and establish a secure, scalable and enterprise-grade cloud data platform supporting analytics, reporting, AI and future digital capabilities. Working closely with Platform Architects, Data Engineers, Enterprise Architects and Business stakeholders, you will define modern cloud data architectures, governance standards and engineering frameworks that enable scalable, trusted and high-quality data products.

Beyond architecture, you will act as a technical coach and platform enabler, helping engineering teams adopt modern cloud data engineering practices, reusable frameworks and enterprise standards. The ideal candidate combines deep technical expertise with strong leadership, excellent communication skills and the ability to produce high-quality architecture documentation.

Requirements:

• 10-15 years of overall IT experience with a strong background in enterprise data architecture and cloud engineering.
• Minimum 6 years of hands-on experience designing and implementing enterprise data platforms on Google Cloud Platform.
• Proven experience architecting and delivering enterprise-scale Cloud Data Platforms on GCP from inception through production.
• Strong expertise in BigQuery architecture, optimisation and enterprise implementation.
• Extensive hands-on experience with dbt, including CI, modular design, testing, documentation and deployment.
• Strong experience designing orchestration frameworks using Apache Airflow (Cloud Composer).
• Proven experience implementing enterprise data ingestion using Fivetran or equivalent cloud ingestion platforms.
• Strong expertise with Dataplex, metadata management, data governance and data lineage.
• Extensive experience designing conceptual, logical and physical data models.
• Strong understanding of Medallion Architecture and modern cloud data architecture principles.
• Deep knowledge of enterprise data governance, data security, privacy, lifecycle management and compliance.
• Strong understanding of CI/CD, DevOps and cloud-native engineering practices.
• Proven experience implementing DataOps, MLOps and LLMOps practices within enterprise cloud platforms.
• Proven experience designing and delivering production-grade AI/ML solutions on Google Cloud Platform, including model deployment, operationalisation, monitoring and lifecycle management.
• Familiarity with Google Cloud AI services such as Vertex AI, Feature Store, Model Registry and AI Pipelines.
• Demonstrated ability to coach and mentor engineering teams while establishing engineering standards and reusable frameworks.
• AI savvy, with the ability to leverage AI-assisted engineering tools to improve productivity, accelerate delivery and increase automation.
• Excellent technical documentation skills with experience producing architecture artefacts and engineering standards.
• Strong analytical, communication and stakeholder management skills.