Director of Data

About the Role

We are seeking a Director of Data to lead the data function and drive the development of scalable, trusted, and business-critical data capabilities across the organisation. You will manage a high-impact team of data scientists, AI Engineers, and MLOps Engineers to ensure enterprise products are powered by high-quality, well-governed, and accessible data.

This is a senior leadership role operating at the intersection of data architecture, governance, platform scalability, and measurable business outcomes. You will play a foundational role in enabling core AI research and development, analytics, and decision intelligence through strong data strategy and execution.

Key Responsibilities

Team Leadership & Technical Management

• Lead and manage a team of data scientists, AI Engineers, and MLOps Engineers.
• Provide technical mentorship and foster a culture of engineering excellence, ownership, and continuous improvement.
• Set clear goals, performance metrics, and growth plans for team members.
• Recruit and retain high-performing data talent across engineering, analytics, and governance disciplines.

Data Strategy & Platform Vision

• Define and own the organisation’s data strategy, including warehouse architecture, ingestion pipelines, and analytics foundations.
• Identify emerging best practices in modern data infrastructure (e.g., real-time streaming, ELT frameworks, data mesh concepts) and assess applicability.
• Champion scalable and reusable data foundations that support both AI innovation and enterprise reporting needs.

Enterprise Data Engineering & Delivery

• Oversee the design and implementation of robust data pipelines for structured and unstructured enterprise data.
• Ensure data systems support product innovation, operational workflows, and AI-native architectures.
• Partner with Product and Engineering leadership to prioritise data initiatives that deliver measurable business value.

Data Pipelines for AI and Model Enablement

• Lead the development and scaling of end-to-end data pipelines that support machine learning and large language model workflows, including training, fine-tuning, evaluation, and inference.
• Ensure high-quality, well-governed datasets are available for model development, including structured business data and unstructured domain-specific documents.
• Partner closely with AI Research and Engineering teams to define data requirements for experimentation, benchmarking, and production deployment.
• Establish repeatable processes for dataset versioning, feature generation, and continuous refresh to support ongoing model improvement.
• Implement strong controls for privacy, anonymisation, and compliance when using enterprise or client-derived data in AI pipelines.

Data Governance, Trust, and Compliance

• Establish strong governance frameworks for data quality, lineage, access controls, and compliance.
• Ensure responsible handling of sensitive enterprise and domain-specific data, aligned with AI ethics and regulatory requirements.
• Define standards for metadata management, documentation, and auditability across all data assets.

Data Enablement for AI and Analytics

• Collaborate closely with AI Engineering and Research teams to ensure data readiness for model training, evaluation, and deployment.
• Enable self-service analytics and trusted reporting across business teams.
• Bridge data engineering with downstream consumption, including dashboards, AI features, and embedded intelligence.

Data Systems Development & Deployment

• Oversee deployment of data platforms and services using best-in-class DataOps and DevOps practices.
• Partner with infrastructure teams to ensure scalability, performance, reliability, and cost efficiency of data systems.
• Contribute to architecture decisions across APIs, backend services, and enterprise integration workflows in the data platform.

Qualifications

Required

• Master’s degree or equivalent experience in Computer Science, Data Engineering, Information Systems, or related field.
• 8+ years of experience in data engineering, analytics platforms, or large-scale data systems.
• 3+ years managing senior technical teams (Data Engineers, Platform Leads, or Analytics Engineering teams).
• Demonstrated ability to build and scale enterprise-grade data infrastructure from strategy through execution.
• Strong experience with modern data stack concepts, API integration, and production backend environments.

Preferred

• Experience in enterprise software or other regulated industries.
• Familiarity with cloud services, containerisation, and distributed data processing frameworks.
• Exposure to AI/ML enablement, feature pipelines, and governance for model training datasets.

Success Metrics

• Scalable and reliable data platform delivery across multiple product lines.
• Improved data quality, governance maturity, and organisational trust in enterprise data.
• Strong enablement of AI initiatives through compliant, model-ready data pipelines.
• Adoption of data-driven decision-making across engineering, product, and business teams.
• Recruitment and development of a high-performing data engineering organisation.

The Offer

• Competitive Salary
• Performance-Based Bonus
• Flexible Working Arrangements
• Professional Development Opportunities
• Great Work Culture