Software Engineer - Market Data (30CB790)

Referment; Greater London; On-site; GBP 70,000 - 110,000; Full time

Job summary

Referment is seeking a hands-on backend/data-platform engineer to work at the intersection of software, data and financial analytics. You will collaborate with pricing quants and risk specialists to bring market data and analytical services into production, while strengthening architecture and reliability.

You will develop market-data services, deepen understanding of financial markets, and create tooling for data governance and scalable analytics.

Qualifications

• Commercial software engineering experience in a data-intensive or financial services environment.
• Strong programming ability in C#, Python, Java or a comparable language.
• Good knowledge of database design, data structures and SQL-based technologies.
• Excellent analytical problem-solving and close attention to detail.
• Ability to manage several active pieces of work and take responsibility for delivery.
• Curious, proactive approach to understanding unfamiliar systems and business problems.

Responsibilities

• Develop, support and productionise market-data services and analytics used within financial technology products.
• Build a detailed understanding of financial markets and how pricing and reference data support quantitative applications.
• Create tools that improve data lineage, governance and reporting.
• Research storage and processing approaches for large datasets, then apply the most appropriate solutions.
• Use a specialist large-scale data language for modelling and analytical workloads.
• Investigate critical production issues with quantitative and engineering stakeholders, identifying practical and durable fixes.
• Contribute proactively to service reliability and ongoing technical improvements.

Skills

C#

Python

Java

SQL

Data analysis

Tools

AWS

Job description

Referment is working with a financial-markets technology business that develops quantitative surveillance and analytics used by major financial institutions. Its products depend on reliable, well-governed market data and the ability to process complex datasets at scale.

This hands-on engineering role sits at the intersection of software, data and financial analytics. You will work alongside pricing quants and risk specialists to bring market data and analytical services into production, strengthen the supporting architecture and solve issues that affect critical systems.

The Role

• Develop, support and productionise market-data services and analytics used within financial technology products.
• Build a detailed understanding of financial markets and how pricing and reference data support quantitative applications.
• Create tools that improve data lineage, governance and reporting.
• Research storage and processing approaches for large datasets, then apply the most appropriate solutions.
• Use a specialist large-scale data language for modelling and analytical workloads.
• Investigate critical production issues with quantitative and engineering stakeholders, identifying practical and durable fixes.
• Contribute proactively to service reliability and ongoing technical improvements.

What We're Looking For

• Commercial software engineering experience, ideally in financial services or another data-intensive environment.
• Strong programming ability in C#, Python, Java or a comparable language.
• Good knowledge of database design, data structures and SQL-based technologies.
• Excellent analytical problem-solving and close attention to detail.
• The ability to manage several active pieces of work and take responsibility for delivery.
• A curious, proactive approach to understanding unfamiliar systems and business problems.

Desirable Experience

Experience with AWS services such as container orchestration, object storage or managed NoSQL databases would be useful, as would prior exposure to market data, pricing or risk systems.

This could suit a backend, data-platform or financial-software engineer who wants to work closer to quantitative users and take responsibility for systems where data quality, traceability and production reliability matter.

#Referment