Platform & Engineering Senior Manager

GSK; Greater London; On-site; GBP 120,000 - 180,000; Full time

Job summary

GSK invites a senior platform and engineering leader to steer Risk Analytics data foundations. You ll own the architecture and roadmap for platforms spanning data engineering pipelines and governance services, ensuring reliable, secure, and scalable foundations for AI-enabled analytics.

You will collaborate with Technology, Privacy, and business partners to secure approvals, standardise patterns, and elevate governance across the data estate.

Qualifications

• Experience designing, delivering, and operating enterprise data platforms and AI infrastructure in production.
• Deep expertise in data engineering, pipelines, cloud platforms, ETL/ELT, APIs, and observability.
• Strong data governance, data classification, lineage, and sensitive-data controls.
• Leadership in architecture, standards, and governance across large-scale data services.

Responsibilities

• Own architecture and roadmap for a platform portfolio, focusing on reliability, security, and scalability.
• Deliver production-grade data pipelines, platforms, governance controls, and shared services.
• Set standards for data modelling, deployment, testing, and production readiness.
• Provide architecture oversight to internal teams and partners, ensuring non-functional requirements.
• Enable AI/analytics product teams by translating data, security, and infra needs into scalable capabilities.

Skills

Enterprise data platforms

Data governance & security

AI enabling infrastructure

Data engineering and pipelines

APIs and orchestration

Observability and reliability

Architecture leadership

Security and access controls

Data modelling and ETL/ELT

Job description

GSK remains committed to achieving bold commercial ambitions for the future. By 2031, we aim to deliver £40 billion in annual sales, leveraging our existing strong performance momentum to significantly increase our positive impact on the health of billions of patients globally. Our Ahead Together strategy is centered on early intervention to prevent and alter the course of disease, thereby protecting people and supporting healthcare systems.

Our diverse portfolio consists of vaccines, specialty medicines, and general medicines. Through continuous innovation and a dedicated focus on scientific and technical excellence, we strive to develop and launch new, groundbreaking treatments that address critical health challenges.

The Risk Analytics and Monitoring (RAM) team supports GSK in establishing a proactive, data-driven compliance culture that aligns with the organisation's strategic priorities and values. Our team delivers actionable insights that enable Legal and Compliance teams to identify emerging risks, focus resources, and make better-informed decisions. Through advanced analytics and responsible application of artificial intelligence, we strengthen risk management, improve Compliance effectiveness, and help position Compliance as a strategic partner to the business.

Role Overview

We are seeking a senior platform and engineering leader to ensure that Risk Analytics products run on trusted data, resilient engineering, and effective technical controls. This role is accountable for the foundations beneath the product portfolio rather than for the business-facing AI and analytics products themselves. The Platform & Engineering portfolio spans two areas:

• Data Engineering and Pipelines covering the design, build, integration, operation, and modernisation of the data analytics pipelines and platforms that supply Risk Analytics products.
• Data Governance and Agent Infrastructure covering data governance, sensitive-data security, identity and access, lineage, retention, and the shared orchestration, telemetry, evaluation, and control services used by AI agents.

You will take primary ownership of one portfolio, based on your expertise and the complementary strengths of the wider team. Success will be measured through platform reliability, data quality, control effectiveness, secure access, operational readiness, and the ability of downstream products to scale without creating avoidable technical or governance risk.

In this role you will

• Own the architecture and operational roadmap for an assigned platform portfolio, prioritising reliability, security, data quality, scalability, technical debt, modernisation, and product dependencies.
• Deliver and operate production-grade foundations across pipelines, integrations, data platforms, governance controls, or shared agent services, with monitoring, support, change control, and lifecycle management.
• Set and enforce technical standards for data modelling, ETL or ELT, APIs, testing, deployment, observability, lineage, access, retention, auditability, resilience, and production support, as relevant to the assigned portfolio.
• Provide architecture assurance and engineering oversight to internal teams and delivery partners, reviewing designs, implementation quality, non-functional requirements, testing evidence, security, and production readiness.
• Enable Compliance Risk Analytics and AI product teams by translating risk analytics 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, secure approvals, and coordinate complex operational change.
• Improve reuse, automation, and cost efficiency by standardising patterns, reducing manual support, simplifying the estate, and strengthening engineering and governance capability through documentation, coaching, and knowledge transfer.

Why you?

Basic Qualifications :

We are looking for professionals with these required skills to achieve our goals:

• 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 the following areas: Data engineering and pipelines, including cloud data platforms, ETL or ELT, APIs, orchestration, data modelling, automated testing, deployment, observability, incident management, and operational reliability.
• Data governance and agent infrastructure, including data classification, identity and access, lineage, retention, metadata, sensitive-data controls, telemetry, evaluation infrastructure, and governance assurance.

Strong architecture and engineering leadership with experience making design decisions, setting standards, managing technical debt, assurance delivery quality, and operating services through their full lifecycle.

Strong technical depth in P