Bulge Bracket Investment Banks

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**Python Quant Data Engineer - Systematic Trading Technology** Build and maintain low-latency data pipelines, collaborate with research and trading teams, and design robust tools for quant research and trading. Key responsibilities include data ingestion, processing, storage, and APIs. Required skills are strong Python, scientific libraries, KDB/Q, data pipelines, and cloud?!native experience. Join JPMorgan Chase as a VP, influencing tech choices and driving business impact in Systematic Equities Trading.

Compensation: Not specified
City: London
Country: United Kingdom

Full Job Description

Location: LONDON, LONDON, United Kingdom

Be an integral part of a technology team that's constantly pushing the envelope to enhance, build, and deliver top-notch technology products.

As a Python Quant Data Engineer you will help build the technology for Systematic Equities Trading Business. The role would sit in the Equities Trading Data & Analytics technology team. As a Vice President Software Engineer at JPMorgan Chase within the agile technology team, you will play a crucial role in improving, developing, and delivering top-tier technology products in a secure, stable, and scalable manner. Your skills and contributions will have a substantial impact on the business, and your profound technical expertise and problem-solving methodologies will be utilized to address a wide range of challenges across various technologies and applications.

Job Responsibilities

Build and support fast, reliable, globally consistent data pipelines (data ingestion, cleaning, backfilling, storing) for the research and execution systems ensuring data integrity and low-latency access for research and trading.
Work with the research and trading teams to onboard new datasets efficiently and consistently for use globally by the business.
Design and build robust tools and frameworks to support quantitative research and production trading.
Design, build and support research infrastructure (e.g. data access APIs, high performant and scalable simulation environments, feature and strategy signal stores)
Build and support research and trading analytics libraries (e.g. markouts, strategy analytics)
Serve as a function-wide subject matter expert in one or more areas of focus
Actively contributes to the engineering community as an advocate of firmwide frameworks, tools, and practices of the Software Development Life Cycle
Influence peers and project decision-makers to consider the use and application of leading-edge technologies

Required Qualifications, Capabilities, And Skills

Design and implementation of front-office systems for quant trading.
Hands-on practical experience delivering system design, application development, testing, and operational stability
Strong expertise in Python. Comfortable with scientific & dataset libraries such as pandas, numpy.
Experience with KDB/Q
Knowledge of data pipelines, market data processing and backtesting workflows.
Advanced knowledge of software applications and technical processes with considerable in-depth knowledge in one or more technical disciplines
Ability to tackle design and functionality problems independently with little to no oversight
Proficiency in automation and continuous delivery methods
In-depth knowledge of the financial services industry and their IT systems
Academic experience in Computer Science, Computer Engineering, Mathematics, or a related technical field
Knowledge of machine learning, statistical techniques and related libraries.

Preferred Qualifications, Skills And Capabilities

Strong knowledge and experience in FIX, Market Data, Analytics, OMS, and equities trading in global markets are assets
Additional knowledge of Java / C++ is a strong plus.
Practical cloud native experience is a plus.
Practical cloud experience is a plus.

Drive significant business impact and tackle a diverse array of challenges that span multiple technologies and applications

Full Job Description

Location: LONDON, LONDON, United Kingdom

Be an integral part of a technology team that's constantly pushing the envelope to enhance, build, and deliver top-notch technology products.

Job Responsibilities

Build and support fast, reliable, globally consistent data pipelines (data ingestion, cleaning, backfilling, storing) for the research and execution systems ensuring data integrity and low-latency access for research and trading.
Work with the research and trading teams to onboard new datasets efficiently and consistently for use globally by the business.
Design and build robust tools and frameworks to support quantitative research and production trading.
Design, build and support research infrastructure (e.g. data access APIs, high performant and scalable simulation environments, feature and strategy signal stores)
Build and support research and trading analytics libraries (e.g. markouts, strategy analytics)
Serve as a function-wide subject matter expert in one or more areas of focus
Actively contributes to the engineering community as an advocate of firmwide frameworks, tools, and practices of the Software Development Life Cycle
Influence peers and project decision-makers to consider the use and application of leading-edge technologies

Required Qualifications, Capabilities, And Skills

Design and implementation of front-office systems for quant trading.
Hands-on practical experience delivering system design, application development, testing, and operational stability
Strong expertise in Python. Comfortable with scientific & dataset libraries such as pandas, numpy.
Experience with KDB/Q
Knowledge of data pipelines, market data processing and backtesting workflows.
Advanced knowledge of software applications and technical processes with considerable in-depth knowledge in one or more technical disciplines
Ability to tackle design and functionality problems independently with little to no oversight
Proficiency in automation and continuous delivery methods
In-depth knowledge of the financial services industry and their IT systems
Academic experience in Computer Science, Computer Engineering, Mathematics, or a related technical field
Knowledge of machine learning, statistical techniques and related libraries.

Preferred Qualifications, Skills And Capabilities

Strong knowledge and experience in FIX, Market Data, Analytics, OMS, and equities trading in global markets are assets
Additional knowledge of Java / C++ is a strong plus.
Practical cloud native experience is a plus.
Practical cloud experience is a plus.

Drive significant business impact and tackle a diverse array of challenges that span multiple technologies and applications

Python Quant Data Engineer - Systematic Trading Technology

Full Job Description

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Full Job Description

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