Lead Data Engineer

Lead Data Engineer
Central London (4 days on site) · Full-time, permanent

About the company
A fast-growing, venture-backed AI start-up building the operating system for modern property management. Its AI assistant automates the operational workload that slows down property managers, letting agents and build-to-rent teams, handling communications, compliance, maintenance coordination and scheduling.

The UK property management services industry is a £33B market that is shifting towards automation. Property teams spend up to 75% of their time on repetitive admin, and the platform is designed to automate 80-90% of those workflows. The product is already live with customers, the feedback has been overwhelmingly positive, and demand is strong as the company scales.

The business is backed by experienced founders, industry advisors and investors. Its goal is clear: to build the defining AI platform for property operations.

The role
We're looking for a Lead Data Engineer to build and lead the data infrastructure behind the platform. You'll architect and scale the systems that power the AI products, from real-time data pipelines and analytics infrastructure to vector databases and machine learning data workflows.

You'll work closely with AI engineers, backend engineers and product teams to make sure the platform can process large volumes of operational data reliably and intelligently.

As the first senior data hire, you'll define the data architecture, tooling and engineering standards, and play a key role in building the foundations of the future data team.

Key responsibilities

• Architect and build scalable data pipelines and infrastructure to support the company's AI and product systems.
• Design and maintain data ingestion, transformation and storage architectures for operational and AI workloads.
• Develop and manage batch and real-time data pipelines.
• Build and optimise systems for vector search, retrieval and ML data pipelines.
• Ensure data reliability, security and governance across the platform.
• Work with the AI and backend engineering teams to support training, inference and product features.
• Implement monitoring, observability and data quality frameworks.
• Optimise the performance of large-scale datasets and query systems.
• Contribute to technical architecture decisions and long-term data strategy.
• Act as the founding data hire, defining the culture, standards and hiring bar for the data function as it scales.
• Partner directly with the founders and product leadership to turn data capabilities into product decisions.

Requirements

Core experience

• 7+ years of experience, mostly in dedicated data engineering roles.
• Strong experience designing and building data pipelines and distributed data systems.
• Experience with relational databases (PostgreSQL preferred; MySQL or similar is acceptable).
• Experience with NoSQL databases.
• Experience with vector databases used in modern AI systems.
• Strong programming experience in Python.
• A proven ability to make and justify architectural decisions, not just implement them.
• A first-class or strong degree in Computer Science, Engineering, Mathematics or a related field.

Highly desirable: data and infrastructure

• Frameworks and infrastructure: Apache Spark, Apache Airflow, Kafka, Elasticsearch / OpenSearch
• Databases: PostgreSQL, MongoDB, and vector databases such as Qdrant, Milvus or pgvector
• Python libraries: Pandas, Polars

Engineering skills

• Experience building scalable backend systems.
• Experience designing data models and storage architectures.
• A strong understanding of data processing performance and optimisation.

Nice to have

• Experience working on AI or machine learning platforms.
• Familiarity with stream processing and event-driven architectures.
• Cloud infrastructure experience (GCP preferred; AWS or Azure also relevant).
• Experience in high-growth or early-stage start-ups.

What we're looking for

• A high-ownership engineer who enjoys building systems from scratch.
• Someone excited to design the data backbone of an AI company.
• Strong problem-solving ability and architectural thinking.
• Comfortable working in a fast-moving start-up environment.
• Motivated by the chance to build technology that transforms an entire industry.

Why join

• Build the data foundations of a category-defining AI company.
• Work directly with the founders and the core engineering team.
• Join at an early stage, with huge ownership and influence.
• Equity, so you share in the upside of what you build.
• Help create the AI infrastructure powering the future of property operations.