Platform & Engineering Senior Manager

Overview

As a senior platform and engineering leader within Risk Analytics and Monitoring, you own the foundation that underpins risk analytics products. You will steer data platforms, governance, and agent infrastructure to ensure reliable, secure, and scalable services for AI-enabled risk analytics. You’ll collaborate with Compliance, Privacy, and delivery partners to translate needs into durable platform capabilities and standards. This role offers the opportunity to shape how data and governance enable proactive, data-driven compliance across a global organisation. You will work in a fast-paced, regulated environment and help position Compliance as a strategic partner.

Responsibilities

• Own architecture and roadmaps for a platform portfolio focusing on reliability, security, data quality, scalability, debt reduction, and dependencies.
• Deliver and operate production-grade data pipelines, platforms, governance controls, and shared agent services with lifecycle management.
• Establish and enforce technical standards for data modelling, ETL/ELT, APIs, testing, observability, lineage, access, retention, and auditability.
• Provide architecture assurance and oversee design quality, non-functional requirements, and production readiness.
• Enable Compliance Risk Analytics and AI product teams by translating data, security, and infrastructure needs into scalable platform capabilities.
• Manage enterprise technical relationships with Technology, Privacy, source-system owners, and delivery partners to resolve dependencies and coordinate changes.
• Improve reuse and cost efficiency through standardisation, automation, and documentation, plus coaching and knowledge transfer.

Key requirements

• Extensive experience designing and operating enterprise data platforms, data engineering capabilities, governance and security frameworks, or AI-enabled infrastructure in production.
• Deep expertise in at least one area: data engineering (cloud platforms, ETL/ELT, APIs, orchestration, data modelling, testing, observability, reliability) or data governance/agent infrastructure (classification, identity and access, lineage, retention, metadata, sensitive-data controls, telemetry, governance assurance).
• Strong architecture and engineering leadership with delivery quality assurance and lifecycle management experience.
• Solid 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 translating security, privacy, regulatory, and business requirements into practical architecture and controls for sensitive data.
• 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
• stakeholder influence
• cross-functional collaboration
• Python
• SQL
• cloud architecture

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