Lead Data Engineer

Overview

As Lead Data Engineer, you will steer data domain engineering within Quilter’s Chief Data Office, shaping scalable, secure data platforms and pipelines. You’ll translate business needs into robust technical designs and promote engineering excellence across teams. You’ll work with cross-functional partners to unlock actionable insights and drive the data strategy forward. This is a chance to influence enterprise-wide data products in a customer-centric, transformation-focused environment.

Pay / Benefits

• Holiday: 26 days
• Pension Scheme
• Private Medical Insurance
• Life Assurance: 4x salary
• Income Protection: 75% of salary
• Quilter Incentive Scheme

Responsibilities

• Provide technical leadership for one or more data domains as engineering authority
• Define and evolve data engineering standards, patterns, and best practices
• Lead design and implementation of scalable data pipelines and data products
• Review architecture and code for quality and alignment with strategy
• Remain hands-on to resolve complex technical challenges and delivery issues
• Lead the technical delivery of key initiatives meeting requirements and principles
• Translate business requirements into detailed technical designs and plans
• Collaborate with PMs, Architects, and stakeholders to prioritise work
• Promote automation, testing, CI/CD, observability, and infrastructure-as-code
• Contribute to roadmap by identifying opportunities, risks, and improvements
• Coach and mentor data engineers; share knowledge and foster learning
• Promote a collaborative, inclusive engineering culture and professional standards
• Partner with product managers, analysts, and governance teams to ensure enterprise alignment
• Communicate complex concepts to technical and non-technical audiences
• Support operational excellence with monitoring, incident management, and data quality governance

Key requirements

• Senior or lead data engineering experience in a complex enterprise
• Hands-on design, development, and support of data platforms using Databricks in Azure
• Experience with batch and real-time data processing and event-driven architectures
• Proven capability to lead technical design and delivery across multiple domains
• Knowledge of data quality frameworks, SLOs, data contracts, and observability tooling
• Strong data governance understanding (lineage, cataloguing, security, access controls)
• Regulatory and information security compliance experience (GDPR, retention)
• Ability to define technical standards and drive adoption across teams
• Mentoring and code review experience; promote engineering excellence
• Experience with data models: Kimball, Data Vault, medallion architecture
• Experience in Agile delivery with cross-functional collaboration
• Strong leadership, communication, and problem-solving skills
• Databricks (Delta Lake, Unity Catalog, Workflows), Microsoft Fabric, Azure data services

• collaborative teammate
• mentoring and knowledge sharing
• strong communicator
• Databricks: Delta Lake, Unity Catalog, Workflows, Notebooks, Spark pipelines
• Microsoft Fabric: Lakehouse, Data Warehouse, Real-Time Intelligence
• Azure: ADLS Gen2, Data Factory, Key Vault, Functions, Monitor

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