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Equities Quant Platform Engineering Lead – Python (Technology) – VP at Citi

London, England, United Kingdom -

Full Time

Start Date

Immediate

Expiry Date

16 Apr, 26

Salary

0.0

Posted On

16 Jan, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Python, Data Engineering, High-Performance Data Stores, Real-Time Streaming Analytics, Cloud Technologies, Developer Experience, Generative AI, HTML5, Equities Cash, Market Mechanics, Low-Latency Programming, Rust, C++

Industry

Financial Services

Description

Architecting scalable, secure re-usable components. Extensive background in delivering production-grade, data-centric applications for quantitative trading and analytics, with demonstrated expertise in: The python data engineering stack (Polars, Parquet, FastAPI, Jupyter, Airflow, Streamlit, Ray) High-performance data stores and query engines (Starburst, Snowflake) Real-time streaming analytics technologies (Kafka, Flink) Cloud container technologies (AWS, Azure, GCP, Docker, Kubernetes) Proven success in enhancing developer experience that reduces friction in coding, building and deploying APIs and client libraries. Real-world application of generative AI prompt engineering and RAG pipelines. Full-stack HTML5 web development skills. Understanding of Equities Cash, D1 & Deriv market mechanics and products via sell-side trading projects Familiarity with low-latency programming languages such as Rust or C++ ------------------------------------------------------ For complementary skills, please see above and/or contact the recruiter. ------------------------------------------------------

Responsibilities

The role involves architecting scalable and secure reusable components for quantitative trading and analytics applications. The candidate will enhance developer experience by reducing friction in coding, building, and deploying APIs and client libraries.