Head of Data Engineering

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 frameworksImprove 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
• PostgreSQL
• 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

• 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, * 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, * Python
• Apache Spark
• Apache Iceberg
• PostgreSQL
• AWS or equivalent cloud platforms
• Data orchestration and workflow automation technologies
• Monitoring and observability platforms
• Modern data platform architectures, * 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