Kalpa Group
Software Engineer - Data Platform - FinTech
Get notified of more jobs like this · No spam, ever
How your CV stacks up
Upload your CV to see how well it fits this job role
?%
Software Engineer – Data Platform – FinTech
TypeScript, Node.js, Airflow, Azure, Python, AI/ML
£100k–£140k + bonus + benefits
Hybrid | Central London
Private-markets data is a mess.
Every private equity fund, credit strategy and infrastructure vehicle reports investor positions differently. Different administrators, formats and reporting cycles. Some APIs are terrible. Many don’t exist at all.
This London fintech is turning that fragmented data into one clean, regulator-ready platform used by wealth managers, private banks and advisers globally.
We’re looking for an experienced software & data engineers to join the data platform team and build the pipelines, data models and access APIs behind it.
You’ll own the full journey of the data: ingesting it from fund administrators and external systems, modelling and reconciling it into a reliable platform layer, then building the APIs that make it available to customer-facing applications, analytics and reporting.
You’ll work on:
- Building and orchestrating ingestion pipelines for complex financial data
- Designing scalable data models across relational, NoSQL, blob and Delta Lake architectures
- Developing production APIs and data services for the wider SaaS platform
- Transforming and reconciling inconsistent structured and unstructured data
- Improving data quality, lineage, observability and platform reliability
- Investigating problems at their source and implementing long-term fixes
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.
TypeScript and Node.js sit at the heart of the wider application stack, including the services and APIs surrounding the data platform. Airflow orchestrates pipelines and workflows, with Python also used across data processing and automation. Everything runs within a modern Azure environment.
This isn’t a siloed data position where you hand datasets over to another engineering team. You’ll work across pipelines, schemas, storage, backend services and APIs, helping determine how data moves through the platform and reaches its users.
Engineers are encouraged to use modern AI tooling throughout the software development lifecycle to accelerate delivery, improve quality and spend more time solving difficult architectural problems.
Get help with your application
Your very own career expert that helps elevate your application to the next level.
You’ll also help develop the platform’s growing AI and machine-learning capabilities, including extracting value from unstructured data and supporting LLM-powered ingestion, reconciliation and reporting workflows.
But the foundation comes first: clean data, robust architecture and reliable production systems.
You’ll probably enjoy working here if you:
- Have strong experience building production data pipelines and data models
- Can build reliable services and APIs around the resulting data
- Are confident with TypeScript and/or Python
- Understand relational, NoSQL and modern cloud-based storage
- Have worked with Airflow or similar orchestration tooling
- Care about data quality, clean engineering and genuine ownership
- Have experience building SaaS products or other production platforms
Experience with Azure, Node.js, data warehousing, Delta Lake or vector databases would be valuable.
You don’t need previous private-markets experience. What matters is strong engineering judgement and the ability to turn messy, real-world data into reliable systems without overengineering them.
“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