At a Glance
- Tasks: Lead global analytics teams to design and deliver high-performance trading solutions.
- Company: Join JPMorgan Chase, a leader in financial technology innovation.
- Benefits: Competitive salary, diverse culture, and opportunities for professional growth.
- Other info: Collaborative environment with strong focus on diversity and inclusion.
- Why this job: Make an impact in real-time trading with cutting-edge AI and data engineering.
- Qualifications: 5+ years in software engineering with expertise in Python/KDB/C++ and AI.
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.
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: J.P. Morgan
At JPMorgan Chase, we pride ourselves on being an exceptional employer, offering a vibrant work culture that fosters innovation and collaboration within our global analytics team. As a Lead Software Engineer, you will benefit from extensive opportunities for professional growth, mentorship, and the chance to work with cutting-edge AI technologies in a fast-paced financial environment. Our commitment to diversity and inclusion ensures that every voice is valued, making it a rewarding place to build your career.
StudySmarter Expert Advice🤫
We think this is how you could land Sr Lead Software Engineer – Data Engineering, Python/C++/KDB/AI
✨Tip Number 1
Network like a pro! Reach out to your connections in the industry, attend meetups, and engage with professionals on platforms like LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving Python, KDB, or AI. This gives potential employers a tangible sense of what you can do and how you can contribute to their team.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. Practice coding challenges and be ready to discuss your past experiences in data engineering and analytics. Confidence is key!
✨Tip Number 4
Don’t forget to apply 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 our 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 you've used these skills in real-world scenarios, especially in fast-paced environments like finance.
Showcase Your AI Knowledge:Since AI is a big part of this role, don’t forget to mention any projects or experiences where you’ve leveraged AI technologies. This could be anything from machine learning models to automation in your development processes.
Be Clear and Concise:When writing your application, keep it straightforward. Use clear language and avoid jargon unless it's relevant. We appreciate a well-structured application that gets straight to the point!
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’s super easy!
How to prepare for a job interview at J.P. Morgan
✨Know Your Tech Inside Out
Make sure you brush up on your Python, KDB, and C++ skills. Be ready to discuss specific projects where you've used these technologies, especially in real-time data processing or analytics. The more you can demonstrate your hands-on experience, the better!
✨Showcase Your AI Knowledge
Since leveraging AI is a big part of this role, prepare examples of how you've applied AI technologies in your previous work. Whether it's machine learning or automation in the SDLC, having concrete examples will set you apart.
✨Prepare for Technical Challenges
Expect to tackle some complex design problems during the interview. Practice explaining your thought process clearly and logically. This will not only show your technical prowess but also your ability to communicate effectively with distributed teams.
✨Emphasise Collaboration and Mentorship
This role involves leading and mentoring teams, so be ready to discuss your leadership style and experiences. Share how you've fostered collaboration in past roles and how you plan to support team members in their growth.
