Lead Data Engineer

Location: Sydney (Hybrid - Tue/Wed/Thu in office)

Industry: InsurTech

Salary: Up to £85,000 (AUD 160,000) + meaningful equity

The Deal: You sort your first 6 months on a working holiday visa, then they take over with full company-paid sponsorship.

The Opportunity: I’m currently working with one of Australia’s fastest-growing insurance and health platforms, who are looking to hire a Data Engineering Lead to own and scale their entire data platform. They’re open to speaking with exceptional UK-based professionals who are excited by the opportunity to relocate to Sydney and be part of a high-growth, AI-driven business. This is a unique opportunity for an ambitious data leader who wants to sit at the intersection of data, AI, analytics, and platform engineering within a high-growth Series A environment. You’ll play a critical role in shaping the foundations that power pricing, claims, operations, product and AI decisioning across the business. You’ll work closely with engineering, product, pricing, operations and AI teams to build clean, trusted, real-time data systems that support automation, experimentation and intelligent decision-making at scale.

My client offers a collaborative, low-ego culture, unlimited AI tooling, meaningful equity upside, and the opportunity to help shape the future of healthcare and insurance through data and AI.

Key Responsibilities:

• Own and scale end-to-end data platform including ingestion, pipelines, warehousing, observability and automation.
• Design and maintain real-time and batch data pipelines across pricing, claims, operations, product and AI systems.
• Build and optimise analytics-ready data models and warehouses using modern tooling such as BigQuery and dbt.
• Partner closely with AI engineers to productionise AI agents and models with clear evaluation frameworks, monitoring and feedback loops.
• Implement robust observability, testing, alerting and fail-safe systems to ensure data reliability and trustworthiness.
• Develop human-in-the-loop workflows and feedback pipelines to improve AI model performance and evaluation.
• Enable teams across the business to self-serve analytics, reporting, experimentation and operational insights.
• Support the development of scalable, secure and maintainable data architecture in a fast-moving environment.

Essential Skills & Experience:

• 5+ years’ experience building and maintaining data platforms or analytics engineering stacks at scale.
• Strong experience with Python and SQL in production data environments.
• Hands-on experience with dbt, modern cloud data warehouses, and event-driven architectures.
• Experience designing reliable batch and/or streaming pipelines with strong observability and testing practices.
• Strong understanding of data modelling, schema design, data contracts and analytics engineering best practices.
• Ability to work cross-functionally with engineering, product, operations and leadership stakeholders.
• Strong communication skills and a proactive, ownership-driven mindset.

Desirable Skills:

• Experience designing evaluation frameworks for AI/LLM systems including offline evaluations, regression testing and monitoring.
• Experience supporting AI agents, ML products or feedback-loop systems.
• Exposure to GCP/BigQuery, Typescript and modern event infrastructure.
• Background within insurance, healthcare, fintech or other regulated environments.
• Experience building real-time operational or pricing systems.

Package & Benefits:

• Up to £85,000 (AUD 160,000) salary + meaningful equity package.
• Hybrid working - 3 days per week in the Sydney office.
• Unlimited AI tooling with no token limits or approval processes.
• Latest MacBook Pro and premium working setup.
• Two company retreats per year.
• Collaborative, high-performing engineering culture.
• Office dogs, unlimited snacks and excellent office environment.
• Opportunity to shape data and AI strategy within a rapidly scaling business.