Prism Digital
Senior Data Engineer
How your CV stacks up
Upload your CV to see how well it fits this job role
?%
Lead & Senior Data Engineers | Python, Vector Databases & AI Data Pipelines | Early Engineer at an AI Platform
Lead Engineer Salary: £80,000 - £110,000
Senior Engineer Salary: £70,000 - £100,000
Equity after probation
Location: Victoria, central London. 4 days a week on-site, Wednesdays from home
There's a particular kind of frustration that comes from watching an entire industry run on spreadsheets, phone calls and email chains long after the technology to fix it exists. That's the gap this company is closing. They've built an AI assistant that takes over the operational grind for property managers, letting agents and build-to-rent teams: the compliance chasing, the maintenance coordination, the scheduling, the endless admin that eats up most of a property manager's week. Pilot customers are already live across thousands of units, and the feedback has been strong enough that the business is now gearing up for its next funding round.
The team sits at 20-30 people globally, with engineering at around 13 and mostly remote outside the core London group. It's a flat set-up: leads are simply the engineers who've earned it, and everyone reports into the Head of Engineering. Data hasn't had a dedicated owner yet, and you'd be joining right at the point where that's being built, working alongside the team defining the architecture rather than dropping into something already set in stone.
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.
Day to day you'll be building and scaling the systems behind the AI product: real-time pipelines, analytics infrastructure, vector databases and the data workflows that feed the machine learning side of the platform. You'll work closely with the AI and backend engineers to make sure the platform can handle serious volumes of operational data reliably, and you'll have real input into the tooling and technical decisions as the function takes shape.
What They're Looking For:
- 5+ years in data engineering or backend engineering
- Strong track record designing and building data pipelines and distributed data systems
- Relational databases (PostgreSQL preferred, MySQL or similar acceptable)
- NoSQL databases
- Vector databases used in modern AI systems
- Strong Python
What You'll Work With:
Get help with your application
Your very own career expert that helps elevate your application to the next level.
- Apache Spark
- Apache Airflow
- Kafka
- Elasticsearch / OpenSearch
- MongoDB
- Vector databases such as Qdrant, Milvus or pgvector
- Pandas and Polars
Nice to Haves:
- JavaScript / Node.js alongside Python
- Experience on AI or machine learning platforms
- Stream processing and event-driven architectures
- Cloud infrastructure (GCP, AWS or Azure)
- Time in a high-growth startup or early-stage company
Why Join / Projects:
You're joining at the point where the data function still has more questions than answers, which means your fingerprints end up on the actual architecture rather than just the code that runs on top of it. You'll get real exposure to the AI and ML side of the business through the vector search and retrieval work, not just traditional pipeline building, and you're close enough to the founders and core engineering team that good ideas don't get lost in layers of process.
If either of these roles sound like something you’d be interested in, please apply!
Senior Data Engineer | Python, Vector Databases & AI Data Pipelines | Early Engineer at an AI Platform
“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