Head of Data Engineering in London

An innovative financial services organisation is seeking a

Head of Data Engineering to lead and scale its data function.

This is a hybrid leadership and hands‑on technical role, offering the opportunity to shape data strategy, drive engineering excellence, and support business‑critical data initiatives.

• The position combines approximately
• 50% people leadership and
• 50% hands‑on engineering

, requiring a leader who can define and execute a strategic roadmap while remaining technically involved in architecture, solution design, and key engineering initiatives.

• Reporting Structure
• Reports directly to a senior executive leadership team member
• High‑profile position with significant influence across the organisation
• Responsible for hiring, performance management, coaching, and team development
• Team Structure
• Lead a team of 3 Data Engineering professionals
• Planned team growth during the next 12 months
• Responsible for fostering a high‑performance, collaborative engineering culture

Key Responsibilities

• Data Strategy & Leadership
• Define and evolve the organisation's data strategy and roadmap in alignment with business objectives
• Balance short‑term business priorities with long‑term scalable architecture decisions
• Drive adoption of data best practices, governance standards, and engineering principles
• Act as the key stakeholder for data‑related decision making across the organisation
• Team Management
• Lead, mentor, and develop a growing Data Engineering team
• Manage hiring processes, onboarding, coaching, and career development
• Conduct performance reviews and establish effective team operating rhythms
• Create a culture of accountability, collaboration, and continuous improvement
• Hands‑On Data Engineering
• Design, build, and maintain scalable data pipelines and data platforms
• Develop datasets, infrastructure, and internal tooling supporting analytics, research, and product initiatives
• Contribute directly to engineering projects where required
• Make architectural decisions and provide technical leadership across the data estate
• Data Quality & Reliability
• Define and own data quality, availability, coverage, and reliability KPIs
• Implement monitoring, alerting, and observability frameworks Improve resilience, validation processes, and incident management procedures
• Ensure data platforms are scalable, secure, and operationally robust
• Cross‑Functional Collaboration
• Partner closely with engineering, product, analytics, and business stakeholders
• Translate business requirements into scalable data solutions
• Enable data‑driven decision making through robust and accessible datasets
• Align technical priorities with organisational goals
• Engineering Excellence
• Establish standards for testing, code quality, documentation, and deployment practices
• Drive operational excellence and continuous improvement initiatives
• Promote modern software engineering principles across the data team
• Ensure sustainable scaling of both technology and team capabilities
• Desired Skills and Experience
• Leadership Experience
• 5-10+ years of Data Engineering experience
• Minimum 2 years of team leadership or management experience
• Proven track record of building, mentoring, and developing engineering teams
• Experience creating and executing technical roadmaps aligned to business goals
• Technical Expertise
• Strong background designing, building, and operating production‑grade data platforms
• Expertise in data pipeline development, orchestration, monitoring, and operational support
• Experience with orchestration tools such as Apache Airflow or equivalent technologies
• Strong software engineering foundations with a focus on maintainability, scalability, and reliability
• Data & Domain Knowledge
• Experience working with complex, large‑scale datasets
• Exposure to financial services, capital markets, investment management, or similarly data‑intensive environments is highly desirable
• Understanding of market data, reference data, time‑series datasets, or comparable analytical domains
• Technology Stack

Experience with several of the following

• Python
• Apache Spark
• Apache Iceberg
• Postgre SQL
• AWS or equivalent cloud platforms
• Data orchestration and workflow automation technologies
• Monitoring and observability platforms
• Modern data platform architectures
• Professional Skills
• Strong communication and stakeholder management capabilities
• Excellent analytical and problem‑solving skills
• Ability to balance strategic thinking with hands‑on delivery
• Pragmatic approach to engineering trade‑off decisions
• Passion for driving continuous improvement and innovation
• Collaborative leadership style with a commitment to diversity, inclusion, and teamwork
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