Lead Data Engineer

• Design and build scalable batch and real-time data pipelines.

• Develop data ingestion, transformation and storage solutions for operational and AI workloads.

• Build and optimise vector search, retrieval systems and ML data pipelines.

• Ensure data reliability, governance, monitoring and observability across the platform.

• Work closely with AI, backend and product teams to support model training, inference and product development.

• Optimise large-scale datasets and database performance.

• Help define engineering standards and mentor future data engineers.

• 7+ years' experience in Data Engineering or Backend Engineering.

• Strong Python development experience.

• Experience building distributed data platforms and scalable pipelines.

• Excellent knowledge of PostgreSQL (or similar relational databases) and NoSQL databases.

• Experience with vector databases such as Qdrant, Milvus or pgvector.

• Familiarity with technologies such as Apache Spark, Airflow, Kafka, Elasticsearch/OpenSearch, Pandas and Polars.

• Strong understanding of data modelling, storage architecture and performance optimisation.

Desirable

• Experience working on AI or Machine Learning platforms.

• Knowledge of cloud platforms (AWS, Azure or GCP).

• JavaScript/Node.js experience.

• Event-driven architecture and stream processing experience.

• Previous experience within a high-growth start-up environment.

• Competitive salary with equity options.

• The opportunity to shape the data architecture of a rapidly growing AI business.

• Work directly alongside founders and senior engineers.

• High levels of ownership, autonomy and technical influence.

• The chance to build technology that is transforming an entire industry.