Head Of Data Engineering

Overview

In this role, you lead the Data Engineering function to build and evolve a modern enterprise data platform. You will shape data products and governance to support regulatory reporting, operations, analytics, and AI capabilities. You work with senior stakeholders to translate the data strategy into tangible business value and ensure a secure, scalable data foundation. This is a strategic, hands-on leadership role in a regulated environment with a focus on transformation and cross‑functional impact.

Pay / Benefits

• discretionary bonus
• matched pension contributions
• 25 days annual leave plus holidays and birthday off
• wellbeing hour
• flexible benefits (Cycle2Work, private healthcare)
• life assurance

Responsibilities

• Lead and develop a high-performing Data Engineering team, fostering engineering excellence
• Drive delivery and ongoing enhancement of the Azure Databricks Enterprise Data Platform
• Establish an in-house data engineering capability with knowledge transfer from partners
• Create scalable data ingestion, transformation, and CI/CD frameworks
• Deliver trusted, governed data products using a modern medallion architecture with strong quality, security and resilience
• Collaborate with Architecture and Data Governance to embed robust models, lineage and ownership
• Partner with Finance, Credit Risk, Operations and Savings to deliver data solutions
• Prioritise work across regulatory, change and operational needs with clear risk/dependency visibility
• Develop team capability through coaching, mentoring and Databricks training
• Manage technology partners, platform performance and retirement of legacy solutions

Key requirements

• Proven experience leading and developing data engineering teams in a complex organisation
• Strong expertise in Azure Databricks and cloud data platforms; modern lakehouse architectures
• Deep knowledge of ETL/ELT, data pipelines, orchestration and data product delivery
• Experience embedding data governance, quality, lineage, security and auditability
• Ability to translate data/tech strategy into business value and outcomes
• Excellent stakeholder management and communication across technical and non-technical audiences
• Experience managing third-party suppliers and transitioning to internal capability
• Track record delivering results in a regulated environment with resource constraints

• Stakeholder management
• Communication
• Influencing skills
• Azure Databricks
• Cloud data platforms
• Lakehouse architectures

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