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.

• 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.

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