At a Glance
- Tasks: Build data pipelines and APIs for a cutting-edge fintech platform.
- Company: Join a dynamic London fintech transforming private-markets data.
- Benefits: Enjoy competitive salary, remote work options, and professional growth.
- Other info: Collaborative environment with opportunities to work on AI and machine learning.
- Why this job: Make a real impact by turning messy data into reliable systems.
- Qualifications: Experience in data engineering, TypeScript, and Python required.
The predicted salary is between 63000 - 77000 £ per year.
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 experienced engineers with a blend of software and data engineering skills 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
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.
You're encouraged to use modern AI tooling throughout the software development lifecycle to accelerate delivery, improve quality and spend more time solving difficult architectural problems. 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.
Software Engineer - Data Platform - FinTech employer: Kalpa Group
Join a dynamic fintech company in Central London that is revolutionising the private-markets data landscape. With a strong emphasis on innovation, collaboration, and employee growth, we offer a hybrid work environment that fosters creativity and flexibility. Our commitment to using cutting-edge technology, including AI and modern cloud solutions, ensures that you will be at the forefront of the industry while enjoying a supportive culture that values your contributions and encourages professional development.
StudySmarter Expert Advice🤫
We think this is how you could land Software Engineer - Data Platform - FinTech
✨Join Local Tech Meetups
Get out there and mingle with fellow developers by joining local tech meetups. It’s a fantastic way to meet people who might be working at Kalpa Group or know someone who does. Plus, you can pick up some trendy tech skills and trends while you're at it!
✨Contribute to Open Source Projects
Show off your coding chops by jumping into open-source projects. Not only does this give you practical experience, but it also gets you noticed in the dev community. You'll create a killer portfolio that speaks volumes about your skills to Kalpa Group.
✨Tap into Online Developer Communities
Don’t underestimate the power of online developer communities like GitHub, Stack Overflow, and even Reddit. Participate in discussions, share your projects, and build your visibility. We can often find opportunities through these channels that can lead to a full-time gig at companies like Kalpa Group.
✨Explore Job Boards Specifically for Tech Roles
Keep your eyes peeled on job boards that focus on tech roles. Sites like TechCareers or Stack Overflow Jobs can often have listings for companies like Kalpa Group that might not show up on broader job sites. Make it a habit to check these regularly, and don’t hesitate to apply directly through our website!
We think you need these skills to ace Software Engineer - Data Platform - FinTech
Some tips for your application 🫡
Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.
Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at Kalpa Group.
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at Kalpa Group and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!
Be clear and concise:When it comes to writing your CV and cover letter, clarity is key. Avoid jargon that could confuse us and stick to simple, direct language. Highlight your achievements with quantifiable results where possible, and keep everything easy to read. A well-organised application goes a long way!
How to prepare for a job interview at Kalpa Group
✨Brush Up on Your Coding Skills
For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.
✨Know Your Tools and Frameworks
Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If Kalpa Group uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.
✨Showcase Your Projects
Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.
✨Prepare for Behavioural Questions
While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.
