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About the Role

As a Lead Data Engineer, you will build and lead the data infrastructure powering an intelligent AI assistant that automates operational workloads for property managers, letting agents and build-to-rent teams. You will architect and scale the data systems behind the AI products, covering real-time data pipelines, analytics infrastructure, vector databases and machine learning data workflows. As the first senior data hire, you will play a key role in defining the data architecture, technology stack, engineering standards and ways of working, and help shape the data team.

Responsibilities

Architect and build scalable data pipelines and infrastructure to support 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 machine learning data pipelines.
Ensure data reliability, security and governance across the platform.
Collaborate with 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 culture, standards and the hiring bar for the data function as it scales.
Partner directly with founders and product leadership to translate data capabilities into product decisions.

Requirements

7+ years of professional experience, with the majority in dedicated data engineering roles.
Strong experience designing and building data pipelines and distributed data systems.
Experience working with relational databases, with PostgreSQL preferred.
Experience working with NoSQL databases.
Experience with vector databases used in modern AI systems.
Strong programming experience in Python.
Demonstrated ability to make and justify architectural decisions.
Experience building scalable backend systems.
Experience designing data models and storage architectures.
Strong understanding of data processing performance and optimisation.
Experience with Apache Spark, Apache Airflow, Kafka, and Elasticsearch or OpenSearch is highly desirable.
Experience with PostgreSQL, MongoDB, and vector databases such as Qdrant, Milvus or pgvector is highly desirable.
Experience with Python data-processing libraries such as Pandas or Polars is highly desirable.
Experience working on AI or machine learning platforms is a plus.
Familiarity with stream processing and event-driven architectures is a plus.
Experience with cloud infrastructure such as GCP, AWS or Azure is a plus.
Experience working in high-growth startups or early-stage companies is a plus.

Skills

Python
PostgreSQL
MySQL
NoSQL databases
Vector databases
Apache Spark
Apache Airflow
Kafka
Elasticsearch
OpenSearch
MongoDB
Qdrant
Milvus
pgvector
Pandas
Polars
GCP
AWS
Azure

Experience Level

7+ years of professional experience

About the Company

At Smart Working, we believe your job should not only look right on paper but also feel right every day.
This isn’t just another remote opportunity - it’s about finding where you truly belong, no matter where you are.
From day one, you’re welcomed into a genuine community that values your growth and well-being.
Our mission is simple: to break down geographic barriers and connect skilled professionals with outstanding global teams and products for full-time, long-term roles.
We help you discover meaningful work with teams that invest in your success, where you’re empowered to grow personally and professionally.
Join one of the highest-rated workplaces on Glassdoor and experience what it means to thrive in a truly remote-first world.