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Sr Lead Software Engineer – Data Engineering, Python/C++/KDB/AI

ExperiencedNo visa sponsorship
J.P. Morgan logo

at J.P. Morgan

Bulge Bracket Investment Banks

Posted 3 days ago

No clicks

**Senior Lead Software Engineer – Data Engineering (Python/C++/KDB/AI)**. Lead global analytics teams, design real-time data pipelines, leverage AI for automation (Python, KDB, C++ expertise required). Mentor team members, influence product design in high-velocity financial environment (5+ years experience, strong AIRouter knowledge, cloud experience preferred). Drive technical excellence in dynamic, global team.

Compensation
Not specified GBP

Currency: £ (GBP)

City
London
Country
United Kingdom

Full Job Description

Location: LONDON, LONDON, United Kingdom

Join a dynamic, global analytics team within JPMorgan Chases Commercial & Investment Bank, Electronic Trading Technology. 

As a Lead Software Engineer at JPMorgan Chase within Commercial & Investment Bank, Electronic Trading Technology, you will play a pivotal role in designing and delivering high-performance, scalable solutions that power real-time trading and research in a fast-paced financial environment. We seek candidates with strong expertise in any of Python/KDB/C++, and who can leverage their knowledge of AI to drive innovation in data engineering, analytics, and automation.

Experience leveraging AI in development, analytics, or SDLC use cases is a critical enabler for this role. 

Job Responsibilities

  • Lead technical initiatives across global analytics teams, providing guidance and direction to engineers, contractors, and vendors in a high-velocity environment.
  • Design, build, and optimize real-time data processing pipelines and applications  ensuring reliability and performance for mission-critical financial systems.
  • Leverage AI technologies and techniques to enhance data engineering workflows, automate SDLC processes, and deliver advanced analytics capabilities for trading and research.
  • Collaborate with research and trading teams worldwide to onboard new datasets efficiently and consistently, supporting global business needs.
  • Build and support robust tools and frameworks for quantitative research and production trading, including scalable APIs and analytics libraries.
  • Mentor and develop team members, manage book of work, and drive continuous improvement in SDLC, testing, and coding standards across distributed teams.
  • Influence product design, application functionality, and technical operations/processes to meet the demands of a rapidly evolving financial landscape.
  • Serve as a subject matter expert in Python, KDB/Q, data engineering, and AI, contributing to firmwide best practices and technical excellence.
  • Champion diversity, inclusion, and collaboration within large, global teams.

 

Required Qualifications, Capabilities, and Skills

  • 5+ years of applied experience in software engineering, in large-scale, fast-paced financial environments.
  • Hands-on experience delivering system design, application development, testing, and operational stability for analytics-driven teams.
  • Strong expertise in any of Python/KDB/C++, for real-time data processing, application development, or data engineering.
  • Working knowledge of AI technologies (machine learning, generative AI, etc.) to support data engineering, analytics, or SDLC automation.
  • Proficiency in automation and continuous delivery methods; advanced understanding of agile methodologies (CI/CD, Application Resiliency, Security).
  • Experience leading and mentoring teams in a global, collaborative environment.
  • Ability to tackle complex design and functionality problems independently and drive solutions across distributed teams.
  • Academic background in Computer Science, Computer Engineering, Mathematics, or a related technical field.

 

Preferred Qualifications, Capabilities, and Skills

  • Experience with market data venue and vendor data platforms.
  • AWS experience; practical cloud native/cloud experience is a plus.
  • Experience with Terraform and Kubernetes for managing production environments in public cloud.
  • Strong knowledge and experience in FIX, Market Data, Analytics, OMS, and equities trading in global markets are assets.
  • Knowledge of machine learning, statistical techniques, and related libraries.
Join our team as a Data Platform Engineer to develop our next-generation Python platform for historical and real-time market data.

Sr Lead Software Engineer – Data Engineering, Python/C++/KDB/AI

Compensation

Not specified GBP

City: London

Country: United Kingdom

J.P. Morgan logo
Bulge Bracket Investment Banks

3 days ago

No clicks

at J.P. Morgan

ExperiencedNo visa sponsorship

**Senior Lead Software Engineer – Data Engineering (Python/C++/KDB/AI)**. Lead global analytics teams, design real-time data pipelines, leverage AI for automation (Python, KDB, C++ expertise required). Mentor team members, influence product design in high-velocity financial environment (5+ years experience, strong AIRouter knowledge, cloud experience preferred). Drive technical excellence in dynamic, global team.

Full Job Description

Location: LONDON, LONDON, United Kingdom

Join a dynamic, global analytics team within JPMorgan Chases Commercial & Investment Bank, Electronic Trading Technology. 

As a Lead Software Engineer at JPMorgan Chase within Commercial & Investment Bank, Electronic Trading Technology, you will play a pivotal role in designing and delivering high-performance, scalable solutions that power real-time trading and research in a fast-paced financial environment. We seek candidates with strong expertise in any of Python/KDB/C++, and who can leverage their knowledge of AI to drive innovation in data engineering, analytics, and automation.

Experience leveraging AI in development, analytics, or SDLC use cases is a critical enabler for this role. 

Job Responsibilities

  • Lead technical initiatives across global analytics teams, providing guidance and direction to engineers, contractors, and vendors in a high-velocity environment.
  • Design, build, and optimize real-time data processing pipelines and applications  ensuring reliability and performance for mission-critical financial systems.
  • Leverage AI technologies and techniques to enhance data engineering workflows, automate SDLC processes, and deliver advanced analytics capabilities for trading and research.
  • Collaborate with research and trading teams worldwide to onboard new datasets efficiently and consistently, supporting global business needs.
  • Build and support robust tools and frameworks for quantitative research and production trading, including scalable APIs and analytics libraries.
  • Mentor and develop team members, manage book of work, and drive continuous improvement in SDLC, testing, and coding standards across distributed teams.
  • Influence product design, application functionality, and technical operations/processes to meet the demands of a rapidly evolving financial landscape.
  • Serve as a subject matter expert in Python, KDB/Q, data engineering, and AI, contributing to firmwide best practices and technical excellence.
  • Champion diversity, inclusion, and collaboration within large, global teams.

 

Required Qualifications, Capabilities, and Skills

  • 5+ years of applied experience in software engineering, in large-scale, fast-paced financial environments.
  • Hands-on experience delivering system design, application development, testing, and operational stability for analytics-driven teams.
  • Strong expertise in any of Python/KDB/C++, for real-time data processing, application development, or data engineering.
  • Working knowledge of AI technologies (machine learning, generative AI, etc.) to support data engineering, analytics, or SDLC automation.
  • Proficiency in automation and continuous delivery methods; advanced understanding of agile methodologies (CI/CD, Application Resiliency, Security).
  • Experience leading and mentoring teams in a global, collaborative environment.
  • Ability to tackle complex design and functionality problems independently and drive solutions across distributed teams.
  • Academic background in Computer Science, Computer Engineering, Mathematics, or a related technical field.

 

Preferred Qualifications, Capabilities, and Skills

  • Experience with market data venue and vendor data platforms.
  • AWS experience; practical cloud native/cloud experience is a plus.
  • Experience with Terraform and Kubernetes for managing production environments in public cloud.
  • Strong knowledge and experience in FIX, Market Data, Analytics, OMS, and equities trading in global markets are assets.
  • Knowledge of machine learning, statistical techniques, and related libraries.
Join our team as a Data Platform Engineer to develop our next-generation Python platform for historical and real-time market data.