Lead Data Engineer

Lead Data Engineer

Want to own the data architecture behind an AI product while the foundations are still being built?

This is an early-stage lead role where you’ll shape the systems powering real-time data, AI workflows, vector search and analytics — with the freedom to make the key technical decisions.

What’s in it for you?

• Own the data architecture and technical direction
• Build the data backbone of an AI-first product from the ground up
• Work closely with AI, backend and product engineers
• Solve problems across streaming, vector search and ML data infrastructure
• Help define tooling, standards and the future data team
• Competitive salary + equity
• Join early enough to have genuine influence over how things are built

What you’ll be doing

• Architecting scalable batch and real-time data pipelines
• Designing ingestion, transformation and storage systems
• Building infrastructure for vector search, retrieval and ML workflows
• Improving data quality, observability and reliability
• Optimising large-scale datasets and query performance
• Supporting AI training, inference and product features
• Making long-term architecture and tooling decisions
• Helping grow and mentor the data engineering function

What you’ll bring

• Strong experience in data engineering or backend engineering
• Experience designing scalable pipelines and distributed data systems
• Strong Python skills
• Experience with relational and NoSQL databases
• Hands-on experience with vector databases
• Good understanding of data modelling, performance and storage architecture
• Experience with technologies such as Spark, Airflow, Kafka or Elasticsearch/OpenSearch

Experience with AI/ML platforms, cloud infrastructure or event-driven architectures would be useful, but you don’t need everything on the list.