At a Glance
- Tasks: Lead innovative software projects in a fast-paced financial environment using Python, KDB, and AI.
- Company: Join JPMorgan Chase's dynamic global analytics team in Electronic Trading Technology.
- Benefits: Competitive salary, diverse work culture, and opportunities for professional growth.
- Other info: Collaborative environment with strong focus on mentorship and continuous improvement.
- Why this job: Make a real impact on trading technology while working with cutting-edge tools and techniques.
- Qualifications: 5+ years in software engineering with expertise in Python/KDB/C++ and AI technologies.
The predicted salary is between 80000 - 100000 £ per year.
Join a dynamic, global analytics team within JPMorgan Chase’s 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.
Sr Lead Software Engineer – Data Engineering, Python/C++/KDB/AI employer: Jpmorgan Chase & Co.
JPMorgan Chase is an exceptional employer, offering a dynamic work environment that fosters innovation and collaboration within its global analytics team. Employees benefit from extensive growth opportunities, mentorship, and the chance to work on cutting-edge technologies in a fast-paced financial setting, all while championing diversity and inclusion. Located in a vibrant financial hub, the company provides a unique platform for professionals to make a meaningful impact in the world of electronic trading technology.
StudySmarter Expert Advice🤫
We think this is how you could land Sr Lead Software Engineer – Data Engineering, Python/C++/KDB/AI
✨Network Like a Pro
Get out there and connect with folks in the industry! Attend meetups, webinars, or even just grab a coffee with someone who works at JPMorgan Chase. Building relationships can open doors that a CV just can't.
✨Show Off Your Skills
When you get the chance to chat with recruiters or during interviews, make sure to highlight your hands-on experience with Python, KDB, and AI. Share specific examples of how you've used these skills to solve real problems in past roles.
✨Prepare for Technical Challenges
Brush up on your coding skills and be ready for technical interviews. Practice common algorithms and data structures, especially those relevant to data engineering. We recommend using platforms like LeetCode or HackerRank to sharpen your skills.
✨Apply Through Our Website
Don't forget to apply directly through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you're genuinely interested in joining the team at JPMorgan Chase.
We think you need these skills to ace Sr Lead Software Engineer – Data Engineering, Python/C++/KDB/AI
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your experience with Python, KDB, and C++. We want to see how your skills align with the role, so don’t be shy about showcasing your AI expertise and any relevant projects you've worked on.
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you’re excited about the role and how your background makes you a perfect fit. Be sure to mention your experience in fast-paced financial environments and your passion for data engineering.
Showcase Your Problem-Solving Skills:In your application, highlight specific examples where you've tackled complex design challenges or led technical initiatives. We love seeing how you’ve driven solutions in previous roles, especially in collaborative settings.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows you’re keen on joining our dynamic team!
How to prepare for a job interview at Jpmorgan Chase & Co.
✨Know Your Tech Inside Out
Make sure you brush up on your Python, C++, and KDB skills. Be ready to discuss specific projects where you've used these technologies, especially in real-time data processing or analytics. Prepare to explain how you've leveraged AI in your previous roles, as this will be a key focus during the interview.
✨Showcase Your Leadership Skills
Since this role involves leading technical initiatives, think of examples where you've guided teams or mentored colleagues. Be prepared to discuss how you’ve influenced product design and improved processes in a fast-paced environment. Highlight your experience in managing work across distributed teams.
✨Understand the Financial Landscape
Familiarise yourself with the financial services industry, particularly in trading and analytics. Be ready to discuss how your technical skills can solve real-world problems in this space. Showing that you understand the business context will set you apart from other candidates.
✨Prepare for Problem-Solving Questions
Expect to tackle complex design and functionality problems during the interview. Practice articulating your thought process when solving technical challenges. Use the STAR method (Situation, Task, Action, Result) to structure your answers and demonstrate your problem-solving abilities effectively.
