Quantitative Data Engineer – Finance Risk & Data Pipelines

TS Imagine; Greater London; On-site; GBP 90,000 - 130,000; Full time

Benefits offered by this job

Vacation and Personal days

Annual bonus and salary review

Training Budget $1,500

Health, dental, life assurance, and ey

care vouchers

Pension scheme

Job summary

TS Imagine, a global leader in trading and risk management, seeks a Quantitative Data Developer for our London office. Design and maintain data solutions for valuing positions and constructing quantitative datasets used in market risk calculations across asset classes.

You will collaborate with Quant Developers on major projects, building high-performance data applications with Python, SQL, and Snowflake, and document methodologies to enable robust validation and transparent analytics.

Qualifications

• M.S. or PhD in mathematics, physical sciences, or engineering preferred.
• 3–5 years of large-scale Python development and data-intensive product experience.
• Experience with financial derivatives and market conventions is essential.
• Live/intraday data experience for curves, volatility surfaces, and risk tools is a plus.

Responsibilities

• Collaborate with Quant Developers on major projects to optimize data pipelines and analytics infrastructure for performance and reliability.
• Design and develop robust data solutions to process inputs for pricing models and market risk calculations across asset classes.
• Develop high-performance, scalable data applications using Python, SQL and Snowflake to analyze large-scale financial datasets.
• Document data methodologies to support internal and external validation processes.

Skills

Python development

SQL programming

C++

Java

Quantitative finance knowledge

Education

M.S. or PhD in mathematics, physical sciences, or engineering

Tools

Snowflake

Job description

TS Imagine, a global leader in trading and risk management, seeks a Quantitative Data Developer for our London office. Design and maintain data solutions for valuing positions and constructing quantitative datasets used in market risk calculations across asset classes.

You will collaborate with Quant Developers on major projects, building high-performance data applications with Python, SQL, and Snowflake, and document methodologies to enable robust validation and transparent analytics.