Head of Engineering – Data Products

Overview

In this role you will own the technical roadmap for the data platform and enterprise-scale AI infrastructure, leading a multi-disciplinary engineering organisation. You will bridge hands-on solution design with vendor accountability, while upholding governance and security standards across global clients. You’ll shape reference architectures, mentor engineers, and collaborate with product and UX teams to deliver scalable, client-focused software. This is a strategic leadership position with a focus on modern data platforms, cloud engineering, and responsible innovation.

Pay / Benefits

• hybrid working in London
• tailorable benefits package
• competitive salary
• Disability Confident scheme
• diversity and inclusion focus
• flexible working arrangements

Responsibilities

• Lead and grow a multi-disciplinary engineering organisation with mentorship and strategic hiring
• Define and own the data platform roadmap and scalable reference architectures
• Guide modern data engineering practices, diagnostics, testing, deployment, and troubleshooting
• Align technical plans with product goals and business forecasts
• Evaluate options, prototype quickly, and de-risk delivery
• Provide architectural oversight and maintain design documentation and reference models
• Foster collaboration across Product, Engineering and UX to build scalable client solutions
• Establish governance for applications and data products including security, privacy and regulatory compliance
• Own platform security posture and incident triage/remediation
• Drive FinOps and cost visibility across cloud environments
• Design repeatable onboarding for tools, analysts, and integrations
• Manage vendor relationships, procurement, and third-party partnerships
• Lead platform modernization and migration programs with risk management
• Stay current with AI/data innovations relevant to enterprise data platforms

Key requirements

• Proven experience leading data engineering or data platform teams at senior/head level in large or matrixed organisations
• Strong background in dimensional data modelling and data pipeline development for web applications
• Hands-on experience with modern cloud data platforms (Databricks, Snowflake) and major cloud providers (Azure, AWS, GCP)
• Understanding of data governance, access control, and security in cloud environments
• Experience with large-scale ETL/ELT design and migration programmes
• Familiarity with AI/ML integration in enterprise data platforms
• Experience with cloud cost management and FinOps practices
• Experience managing vendor contracts, procurement, and commercial negotiations
• Strong stakeholder management and ability to communicate across technical and non-technical audiences
• Structured, specification-driven approach to requirements and delivery
• Evidence of applying technology to solve business problems
• Ability to work in an agile environment
• Excellent communication and collaboration skills

• Leadership and people management
• Stakeholder管理 and cross-functional collaboration
• Strategic thinking and problem solving
• Azure Databricks/Spark with Python
• Snowflake or equivalent
• Azure, AWS, or GCP cloud fundamentals

…