Software Engineer - Data Platform - FinTech

Kalpa Group; Greater London; Hybrid; GBP 90,000 - 120,000; Full time

Job summary

Kalpa Group is seeking an experienced Software Engineer to join the Data Platform team in a hybrid role based in Central London. You will own end-to-end data journeys—from ingestion with fund administrators to modeling and exposing reliable APIs for customer-facing applications and analytics.

The ideal candidate has deep experience building production data pipelines and scalable data models, with proficiency in TypeScript and Python, and a strong understanding of Azure-based data tooling.

Qualifications

• Experience building production data pipelines and data models.
• Strong knowledge of relational and NoSQL data stores and data warehousing concepts.
• Experience with SaaS platforms or production data platforms is a plus.

Responsibilities

• Build and orchestrate ingestion pipelines for financial data.
• Design scalable data models across relational, NoSQL, blob and Delta Lake.
• Develop production APIs and data services for the SaaS platform.
• Improve data quality, lineage, observability and reliability of the platform.
• Collaborate on AI and ML data workflows and production tooling.

Skills

Data engineering

Software engineering

Distributed systems

Problem solving

Tools

TypeScript

Python

Azure

Airflow

Delta Lake

SQL

NoSQL

Job description

Software Engineer – Data Platform – FinTech

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 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 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.

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.