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.