Lead Data Engineer

• Architect and build scalable data pipelines and distributed data systems
• Design ingestion, transformation and storage patterns for operational and AI workloads
• Deliver batch and real-time/streaming pipelines
• Build and optimise vector search and retrieval pipelines that support AI features
• Implement monitoring, observability and data quality frameworks
• Drive security, reliability and governance across the data layer
• Partner closely with backend and AI engineers to support training, inference and product delivery
• Influence technical direction and help shape the future data team as the company scales

• Demonstrable experience in data engineering or backend engineering with proven architecture ownership
• Good level of Python engineering skills
• Strong relational database experience (PostgreSQL preferred) including performance and query optimisation
• Exposure to NoSQL systems
• Comfortable building from scratch in a fast-moving, product-led environment
• Experience with vector databases and vector search in modern AI systems
• Desirable: Spark, Airflow, Kafka, Elasticsearch/OpenSearch, event-driven architectures
• Cloud experience (AWS, GCP or Azure) is a plus

Why join

• High impact and ownership as an early senior hire
• Work with a strong engineering team on real AI product challenges
• Competitive salary

A high-growth AI software company is looking for a Lead Data Engineer to own and scale the data foundations behind an AI-driven operations platform used by property teams. This is a hands-on, high-ownership role where you'll define the data architecture, set engineering standards and build systems that power product analytics and modern AI capabilities.