Data Engineer

Purpose of role:

• This Data Engineer is a senior individual contributor responsible for leading the design, delivery, and operational support of complex, business‑critical data pipelines integrating investment and financial market data across multiple vendors and platforms.
• In addition to hands‑on delivery, the role carries accountability for technical leadership, including mentoring junior and mid‑level Data Engineers, promoting best practices, and maintaining high standards of engineering quality across the team.
• This Data Engineer is expected to lead solution design discussions, drive stakeholder collaboration, and take ownership of complex integration and data engineering initiatives within a hybrid on‑premises and multi‑cloud environment.
• This role represents the natural career progression from Mid‑Level Data Engineer and is characterised by increased autonomy, higher delivery capacity, and responsibility for more complex or strategically important work. It carries the accountability for the technical outcomes of delivery and has a career progression towards the Lead Data Engineer or Data Architect.

Duties and responsibilities:
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.

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.

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

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.

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.

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.