Arrows
Lead Data Engineer
How your CV stacks up
Upload your CV to see how well it fits this job role
?%
Job Opportunity: Lead Data Engineer
I'm currently partnered with an early-stage, well-funded AI business that is building the operating system for a large, traditionally under-digitised industry, and looking to hire their first Lead Data Engineer into a small, high-impact team.
This is a broad and genuinely technical role sitting at the heart of the data function, responsible for architecting and scaling the systems powering their AI products. Already live with pilot customers managing 14,000+ units, this is a rare opportunity to join early and own the data architecture from day one, working closely with AI engineers, backend engineers and product teams to translate business needs into real-time, AI-ready data infrastructure.
The environment suits someone who enjoys building from scratch, takes pride in architectural rigour, and wants to be the defining technical voice behind a company's data foundations as it scales toward a category-defining AI platform.
Reasons to use Rodeo
Start with a chat, not a search bar
Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.
It searches the market for you
Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
What you'll be doing:
- Architecting and building scalable data pipelines and infrastructure to support AI and product systems
- Designing data ingestion, transformation and storage architectures for operational and AI workloads
- Developing and managing batch and real-time data pipelines
- Building and optimising systems for vector search, retrieval and ML data pipelines
- Ensuring data reliability, security and governance across the platform
- Implementing monitoring, observability and data quality frameworks
- Contributing to technical architecture decisions and long-term data strategy
- Helping build and mentor the future data engineering team as the company scales
Get help with your application
Your very own career expert that helps elevate your application to the next level.
Tech stack includes:
- Python
- PostgreSQL
- MongoDB
- Vector databases (Qdrant, Milvus or pgvector)
- Apache Spark
- Apache Airflow
- Kafka
- Elasticsearch/OpenSearch
- Pandas
- Polars
What they're looking for:
- 7+ years of experience in data engineering or backend engineering
- Strong experience designing and building data pipelines and distributed data systems
- Experience with relational databases (PostgreSQL preferred) and NoSQL databases
- Experience with vector databases used in modern AI systems
- Strong programming experience in Python
- Comfortable working in a fast-moving, high-ownership startup environment
“It took my CV and asked me questions relevant to understanding what kind of jobs to suggest for me. Suggestions were almost perfect. Jobs were exactly what I’ve been looking for.”
Jessica, London
Skills
Location