Quantitative Data Engineer – Real-Time Finance Pipelines

Referment; Greater London; On-site; GBP 70,000 - 95,000; Full time

Job summary

Referment is seeking a Quantitative Data Developer for its London office to build data solutions supporting valuation and quantitative datasets such as curves and volatility cubes. You will optimize data pipelines and analytics infrastructure for performance and reliability, enabling real-time pricing and market-risk calculations across multiple asset classes.

Working hands-on with Python, SQL and Snowflake, you will transform large-scale financial data, perform quality checks, and document

Qualifications

• 3-5 years developing large-scale Python and writing SQL for data-intensive products.
• Experience with C++ or Java is a plus.
• Strong understanding of financial derivatives and market conventions.
• Familiar with yield curves, inflation curves, volatility surfaces and interest rate data.

Responsibilities

• Discover, design, develop and maintain data solutions for valuation and quantitative datasets.
• Optimize data pipelines and analytics infrastructure for performance and reliability.
• Build robust systems delivering inputs for pricing and market-risk calculations in real time.
• Document data methodologies clearly to support validation.

Skills

Python

SQL

C++

Java

Data pipelines

Education

MS or PhD in mathematics / physical sciences / engineering

Tools

Snowflake

Job description

Referment is seeking a Quantitative Data Developer for its London office to build data solutions supporting valuation and quantitative datasets such as curves and volatility cubes. You will optimize data pipelines and analytics infrastructure for performance and reliability, enabling real-time pricing and market-risk calculations across multiple asset classes.

Working hands-on with Python, SQL and Snowflake, you will transform large-scale financial data, perform quality checks, and document