Data Principal Engineer

Job Description

About the Role

We are a young, dynamic, hyper-growth company looking for smart, creative, hard-working people with integrity to join us!

• Ecosystem Architecture & Platform Simplification:
• Produce a definitive, up-to-date master blueprint of the Group's data architecture, sources, flows, models, KPI mappings and use it to drive a structured simplification programme; cutting over-engineering and technical debt, standardising technology choices across teams, and making it faster to deliver new data products.
• Real-Time Operational Enablement:
• Logistics, Supply Chain, and Distribution Centre operations need faster access to operational data than our current batch-oriented warehouse provides.
• Design and build the event-driven, live data layer that decouples these systems from the historical reporting warehouse, enabling faster and more precise operational analytics across the Group.
• Data Governance Standards & Documentation:
• Establish and own the technical standards that underpin the Group's data governance programme.
• Defining data quality standards, lineage documentation requirements, and data management practices, and building them into sprint workflows as normal engineering practice.
• Working with central team SMEs (Data Engineering, Analytics Engineering, BI, Data Ops) to turn existing engineering practice into formal, Group-level domain standards.
• Building and maintaining a centralised architecture repository as the Group's single source of truth for how data flows across the ecosystem. Given the scale involved, hundreds of systems across 15-20+ business units. This is a phased build: the first 90 days should produce the repository's structure and the first few highest-priority domains, with full coverage growing over the following quarters.
• Keeping standards and documentation current as the platform evolves.
• AI Enablement, Integration & Automation Platform:
• Define the technical guardrails that let teams innovate safely: data contracts, security and privacy controls, model governance patterns, and clear standards for embedding automation into data engineering operations.
• Own platform alignment for AI consumption, so Big Query, Dataform, and Looker expose data that AI tools and copilots can use reliably and safely: documented schemas, semantic layers, data contracts, consistent access patterns.
• Lead integration planning for AI tooling on the platform, secure, well-governed connection patterns for AI agents, in line with the Group's AI Data Policy.
• Design and build automation that keeps governance and platform operations manageable as the Group scales, automated maturity telemetry from platform metadata (classification tag coverage, lineage completeness, Dataform test coverage, Looker documentation completeness), self-service onboarding tooling, and AI-assisted copilots that cut manual facilitation work across the Group.
• Technical Onboarding, Training & Knowledge Transfer:
• Replace fragmented, course-heavy onboarding with a structured learning path and reference architecture guides tailored to different skill levels (engineering, analytics, BI).
• Design specialist technical training modules covering architecture and standards, and contribute content into the Group's tiered governance training.
• Success here means the team can operate without depending on any one person's knowledge.
• Technical Leadership & Mentorship:
• As the highest individual contributor in the data domain, you weigh in on design disagreements, unblock the most complex cross-functional challenges, and set the engineering standard for the division.
• Where a technical recommendation conflicts with a team's delivery priorities, the accountable manager makes the final call, your job is to bring the strongest technical case to that decision.
• You coach and mentor senior and staff-level engineers, advise the Engineering Director on platform and governance strategy, and contribute to the technical career path matrix for the department.
• Minimum Required
  
  Qualification:
• A Bachelor's degree in Computer Science, Engineering, Information Systems, or a related field is preferred; equivalent demonstrated experience at this scale and seniority…