Platform & Engineering Senior Manager

In this senior role, you will own the architecture and roadmap for a data platform portfolio within Risk Analytics and Monitoring, ensuring reliable, secure, and scalable foundations. You will partner with cross-functional teams to translate risk, data, and governance needs into robust platform capabilities. Your work drives compliant and high-quality data infrastructure that enables AI-driven risk analytics while reducing technical and governance risk. This is a strategic, impact-focused opportunity in a global, regulated environment.

• Own the architecture and operational roadmap for an assigned platform portfolio, prioritising reliability, security, data quality, scalability, technical debt, modernisation, and dependencies.
• Deliver and operate production-grade foundations across pipelines, data platforms, governance controls, or shared agent services, with monitoring, change control, and lifecycle management.
• Set and enforce technical standards for data modelling, ETL/ELT, APIs, testing, deployment, observability, lineage, access, retention, auditability, resilience, and production support.
• Provide architecture assurance and engineering oversight to internal teams and delivery partners, reviewing designs, non-functional requirements, testing evidence, security, and production readiness.
• Enable Compliance Risk Analytics and AI product teams by translating data, integration, security, and infrastructure needs into scalable platform capabilities.
• Lead enterprise technical relationships with Technology, Privacy, source-system owners, and delivery partners to resolve dependencies and coordinate operational change.
• Improve reuse and cost efficiency by standardising patterns, reducing manual support, and strengthening engineering and governance through documentation, coaching, and knowledge transfer.

• Significant experience designing, delivering, and operating enterprise data platforms, data engineering capabilities, governance and security frameworks, or AI-enabling infrastructure in production.
• Deep expertise in at least one of: data engineering and pipelines (cloud platforms, ETL/ELT, APIs, orchestration, testing, deployment, observability, incident management, reliability) or data governance and agent infrastructure (classification, identity and access, lineage, retention, metadata, telemetry, governance assurance).
• Strong architecture and engineering leadership with lifecycle management and delivery quality assurance experience.
• Strong technical depth in Python, SQL, cloud architecture, APIs, enterprise integration, security patterns, and modern engineering practices; able to guide teams without being the primary developer.
• Experience with sensitive or regulated data and translating security, privacy, regulatory, and business requirements into practical architecture and controls.
• Proven ability to lead complex cross-functional delivery and influence senior stakeholders in a global matrix organization.
• Advanced knowledge gained through a degree or equivalent professional experience in computer science, data engineering, software engineering, information security, data governance, analytics, or related discipline.

• leadership in a matrix organization
• stakeholder influence
• strong communication
• Python
• SQL
• cloud architecture