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Job Details

J.P. Morgan logo
Bulge Bracket Investment Banks

Systematic Trading - Python Quant Data Engineer - Vice President

at J.P. Morgan

ExperiencedNo visa sponsorship

Posted 17 days ago

No clicks

Senior Lead Software Engineer within Equities Electronic Trading at JPMorgan Chase responsible for building and supporting low-latency, globally consistent data pipelines and research/trading infrastructure. You will onboard datasets, design data access APIs, build high-performance simulation environments, and develop analytics libraries and tooling to support quantitative research and production trading. The role emphasizes strong Python and KDB/Q expertise, knowledge of market data processing and backtesting workflows, and experience delivering front-office quant trading systems.

Compensation
Not specified

Currency: 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 Sr Lead Software Engineer at JPMorgan Chase within the Equities Electronic Trading 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

Job Details

J.P. Morgan logo
Bulge Bracket Investment Banks

17 days ago

clicks

Systematic Trading - Python Quant Data Engineer - Vice President

at J.P. Morgan

ExperiencedNo visa sponsorship

Not specified

Currency not set

City: London

Country: United Kingdom

Senior Lead Software Engineer within Equities Electronic Trading at JPMorgan Chase responsible for building and supporting low-latency, globally consistent data pipelines and research/trading infrastructure. You will onboard datasets, design data access APIs, build high-performance simulation environments, and develop analytics libraries and tooling to support quantitative research and production trading. The role emphasizes strong Python and KDB/Q expertise, knowledge of market data processing and backtesting workflows, and experience delivering front-office quant trading systems.

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 Sr Lead Software Engineer at JPMorgan Chase within the Equities Electronic Trading 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