Bulge Bracket Investment Banks

Posted 10 days ago

No clicks

**Lead Software Engineer (Quant Developer) – Push Tech Limits at JPMorgan Chase** In Athens, Greece, shape next-gen trading analytics as a Lead Software Engineer (Quant Developer). You'll design, develop, and maintain secure, scalable systems using KDB+/Q and Python. Lead technically and mentor junior team members, driving AI-assisted engineering adoption. Requires advanced software engineering experience, proficiency in KDB+/Q, Python, andSDLC tools, plus a relevant degree. Preferred skills include cloud familiarity, data science libraries, and trading context understanding. Join a collaborative, global team, directly impacting market data understanding and actions at JPMorgan Chase.

Compensation: Not specified
City: Athens
Country: Greece

Full Job Description

Location: Athens, Attica, Greece

We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible. Join a team where your contributions directly influence how the firm understands and acts on market data at scale. You'll work alongside talented engineers and quantitative professionals who are passionate about building cutting-edge solutions in a collaborative, inclusive environment where growth and innovation are encouraged.

As a Lead Software Engineer (Quant Developer) at JPMorganChase within the Commercial & Investment Bank's Electronic Trading Data Analytics team, you will be an integral part of an agile, global team building and enhancing trusted, market-leading technology products in a secure, stable, and scalable way. You will work on greenfield projects that analyze large volumes of data generated by the firm's trading engines, playing a pivotal role in shaping the next generation of analytics applications within the Equities division. As a core technical contributor, you will drive critical technology solutions across multiple technical areas in support of the firm's business objectives.

Job Responsibilities

Design and execute creative software solutions, including architecture, development, and technical troubleshooting, thinking beyond conventional approaches to solve complex problems
Develop secure, high-quality production code while reviewing and debugging code written by others to maintain engineering excellence
Build and maintain core systems and frameworks using KDB+/Q and Python, ensuring reliability and performance at scale
Serve as a subject matter expert in one or more areas of focus, providing technical guidance across the broader engineering community
Actively champion firmwide frameworks, tools, and Software Development Life Cycle practices as an advocate within the engineering community
Mentor junior team members, fostering a culture of learning, growth, and technical excellence
Partner with the Product team to translate new business requirements into scalable, well-designed technical solutions
Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test strategy acceleration, incident/root-cause analysis support), while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team
Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation
Contribute to a team culture grounded in diversity, inclusion, opportunity, and mutual respect

Required Qualifications, Capabilities, and Skills

Formal training or certification on software engineering concepts and advanced applied experience
Hands-on practical experience delivering system design, application development, testing, and operational stability
Advanced proficiency in KDB+/Q and Python for building and maintaining production-grade systems
Proficiency across all aspects of the Software Development Life Cycle
Advanced understanding of agile methodologies, including CI/CD, application resiliency, and security practices
Degree in Computer Science, Computer Engineering, Mathematics, or a related technical field
Hands-on experience using enterprise-authorized AI-assisted software development tools within the work environment (e.g., for coding, test creation, troubleshooting, or documentation) with demonstrated ability to critically evaluate, validate, and refine AI-generated outputs for correctness, performance, and security
Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; ability to guide peers on safe and effective usage within team practices

Preferred Qualifications, Capabilities, and Skills

Familiarity with cloud infrastructure (AWS) and containerization technologies
Experience with Python data and scientific computing packages such as pandas, polars, NumPy, SciPy, or PyTorch
Experience working with tick data and real-time data feeds in a trading or financial markets context
Familiarity with workflow orchestration tools such as Airflow or pykx for building data pipelines
Experience with C++ for building low-latency components
Familiarity with FIX protocol, order types, and equities market microstructure

Shape next-generation trading analytics and drive real impact within a global, agile Equities engineering team.

Full Job Description

Location: Athens, Attica, Greece

Job Responsibilities

Design and execute creative software solutions, including architecture, development, and technical troubleshooting, thinking beyond conventional approaches to solve complex problems
Develop secure, high-quality production code while reviewing and debugging code written by others to maintain engineering excellence
Build and maintain core systems and frameworks using KDB+/Q and Python, ensuring reliability and performance at scale
Serve as a subject matter expert in one or more areas of focus, providing technical guidance across the broader engineering community
Actively champion firmwide frameworks, tools, and Software Development Life Cycle practices as an advocate within the engineering community
Mentor junior team members, fostering a culture of learning, growth, and technical excellence
Partner with the Product team to translate new business requirements into scalable, well-designed technical solutions
Drives team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes (e.g., AI-assisted code review/refactoring, test strategy acceleration, incident/root-cause analysis support), while establishing consistent validation standards (secure coding, peer review, automated testing) and promoting reuse of effective patterns across the team
Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation
Contribute to a team culture grounded in diversity, inclusion, opportunity, and mutual respect

Required Qualifications, Capabilities, and Skills

Formal training or certification on software engineering concepts and advanced applied experience
Hands-on practical experience delivering system design, application development, testing, and operational stability
Advanced proficiency in KDB+/Q and Python for building and maintaining production-grade systems
Proficiency across all aspects of the Software Development Life Cycle
Advanced understanding of agile methodologies, including CI/CD, application resiliency, and security practices
Degree in Computer Science, Computer Engineering, Mathematics, or a related technical field
Hands-on experience using enterprise-authorized AI-assisted software development tools within the work environment (e.g., for coding, test creation, troubleshooting, or documentation) with demonstrated ability to critically evaluate, validate, and refine AI-generated outputs for correctness, performance, and security
Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; ability to guide peers on safe and effective usage within team practices

Preferred Qualifications, Capabilities, and Skills

Familiarity with cloud infrastructure (AWS) and containerization technologies
Experience with Python data and scientific computing packages such as pandas, polars, NumPy, SciPy, or PyTorch
Experience working with tick data and real-time data feeds in a trading or financial markets context
Familiarity with workflow orchestration tools such as Airflow or pykx for building data pipelines
Experience with C++ for building low-latency components
Familiarity with FIX protocol, order types, and equities market microstructure

Shape next-generation trading analytics and drive real impact within a global, agile Equities engineering team.

Lead Software Engineer (Quant Developer)

Full Job Description

SIMILAR OPPORTUNITIES

Lead Software Engineer - Quantitative Portfolio Construction Development

Lead Quantitative Engineer