Head of Data Architecture & Enablement

Head of Data Architecture & Enablement

DUTIES & RESPONSIBILITIES

1. Advanced Data Engineering & Solution Delivery

• Lead the design and implementation of complex, large-scale data pipelines integrating market, reference, and investment data.
• Solve advanced data engineering challenges, including high-volume processing, complex transformations, reconciliation, and performance optimisation.
• Ensure delivered solutions are scalable, resilient, secure, and fit for purpose in a regulated financial environment.

2. Technical Leadership & Standards

• Act as a technical authority within the Data Engineering team, promoting best practices in coding, testing, deployment, and operational support.
• Review designs, code, and implementations produced by junior and mid-level engineers to ensure quality and consistency.
• Contribute to the evolution of data engineering standards, patterns, and reusable frameworks.

3. Mentoring & Capability Development

• Coach and mentor junior and mid-level Data Engineers in data engineering techniques, tools, and the firm’s technology stack.
• Provide guidance on problem-solving approaches, solution design, and operational readiness.
• Support the professional growth and technical maturity of the broader Data Engineering function.

4. Stakeholder Leadership & Collaboration

• Lead technical engagement with business stakeholders, architects, and analysts to refine requirements and shape viable data engineering solutions.
• Translate complex business and regulatory requirements into clear technical designs and delivery plans.
• Act as a trusted technical partner to front-office, middle-office, and back-office stakeholders.

5. Platform, Architecture & Governance Alignment

• Work closely with Data Architects and IT Architects to ensure solutions align with enterprise architecture, integration patterns, and data models.
• Ensure pipelines meet data governance, lineage, auditability, and regulatory expectations.
• Balance delivery speed with control, resilience, and long-term maintainability.

6. Operational Excellence

• Take ownership of production pipelines, ensuring monitoring, alerting, and support processes are in place.
• Lead root-cause analysis of complex production issues and implement durable fixes.
• Drive continuous improvement in pipeline reliability, performance, and supportability.

REQUIRED EXPERIENCE

• 8–10 years’ experience in data engineering within complex enterprise environments.
• Track record of leading the delivery of complex data integration initiatives.
• Modern programming skills (high or low level) in Data Integration frameworks such as Synatic, n8n or similar, or, Python, Java or JavaScript.
• Advanced experience with ETL/ELT frameworks, orchestration tools, and scheduling platforms.
• Solid understanding of hybrid on-premises and cloud-based data architectures (AWS).
• Strong understanding of integration patterns, performance optimisation, and data quality frameworks.

Advantageous experience:

• Financial services experience (asset management, fund services, banking, insurance) in a similar role, or at a vendor provisioning services to this industry.
• Experience working with AWS technology

REQUIRED QUALIFICATIONS

• Tertiary qualification in Computer Science, Information Systems, Information Technology, Engineering, or similar.
• AWS certifications advantageous.

KEY COMPETENCIES

• Demonstrated ability to mentor and uplift less-experienced engineers.
• Strong stakeholder engagement and facilitation skills.
• Clear and structured communication, both technical and non-technical.
• High level of ownership, accountability, and attention to detail.
• Deep understanding of data engineering solutions applicable to investment data domains (e.g., pricing, reference data, positions, trades, NAVs).
• Familiarity with front-office, middle-office, and back-office data flows.
• Awareness of regulatory, audit, and risk considerations impacting financial data processing.
• Advanced skill with engineering data pipelines.