Glocomms
Head of Data Engineering
City of London
Posted about 21 hours ago
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Overview
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
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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
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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
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Skills
Data Engineering
Team Leadership
Data Strategy
Data Architecture
Python
Apache Spark
Apache Iceberg
PostgreSQL
AWS
Apache Airflow
Data Pipeline Development
Data Governance
Stakeholder Management
Software Engineering
Data Quality
Observability