Lead Software Engineer – Data Engineering, Python/KDB at JPMC Candidate Experience page

Singapore, Singapore, Singapore -

Full Time

Start Date

Immediate

Expiry Date

03 Sep, 26

Salary

0.0

Posted On

05 Jun, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Python, KDB/Q, AI, Data Engineering, System Design, CI/CD, Agile Methodologies, AWS, Terraform, Kubernetes, Machine Learning, Generative AI, Real-time Data Processing, API Development, Financial Systems, Mentoring

Industry

Financial Services

Description

We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible. As a Lead Software Engineer at JPMorganChase within the Electronic Trading Technology team, 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, 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 * Bachelor’s degree in computer science, Engineering, Mathematics, or other related disciplines * 5+ years of applied experience in software engineering, preferably 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, 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. J.P. Morgan is a global leader in financial services, providing strategic advice and products to the world’s most prominent corporations, governments, wealthy individuals and institutional investors. Our first-class business in a first-class way approach to serving clients drives everything we do. We strive to build trusted, long-term partnerships to help our clients achieve their business objectives. We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants’ and employees’ religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs [https://careers.jpmorgan.com/us/en/how-we-hire/faqs] for more information about requesting an accommodation. J.P. Morgan’s Commercial & Investment Bank is a global leader across banking, markets, securities services and payments. Corporations, governments and institutions throughout the world entrust us with their business in more than 100 countries. The Commercial & Investment Bank provides strategic advice, raises capital, manages risk and extends liquidity in markets around the world.

Responsibilities

Lead the design and optimization of high-performance real-time data processing pipelines for electronic trading and research. Leverage AI technologies to automate SDLC processes and provide technical guidance to global analytics teams.