At a Glance
- Tasks: Build and support data pipelines for systematic equities trading using Python.
- Company: Join J.P. Morgan, a global leader in financial services.
- Benefits: Competitive salary, diverse culture, and opportunities for professional growth.
- Other info: Dynamic team environment with a focus on innovation and collaboration.
- Why this job: Make a real impact in the fast-paced world of finance and technology.
- Qualifications: Strong Python skills and experience in quantitative trading systems required.
The predicted salary is between 80000 - 100000 £ per year.
Be an integral part of a technology team that's constantly pushing the envelope to enhance, build, and deliver top-notch technology products. As a Python Quant Data Engineer you will help build the technology for Systematic Equities Trading Business. The role would sit in the Equities Trading Data & Analytics technology team. As a Vice President Software Engineer at JPMorgan Chase within the agile technology team, you will play a crucial role in improving, developing, and delivering top-tier technology products in a secure, stable, and scalable manner. Your skills and contributions will have a substantial impact on the business, and your profound technical expertise and problem‑solving methodologies will be utilized to address a wide range of challenges across various technologies and applications.
Job Responsibilities
- Build and support fast, reliable, globally consistent data pipelines (data ingestion, cleaning, backfilling, storing) for the research and execution systems ensuring data integrity and low‑latency access for research and trading.
- Work with the research and trading teams to onboard new datasets efficiently and consistently for use globally by the business.
- Design and build robust tools and frameworks to support quantitative research and production trading.
- Design, build and support research infrastructure (e.g. data access APIs, high performant and scalable simulation environments, feature and strategy signal stores).
- Build and support research and trading analytics libraries (e.g. markouts, strategy analytics).
- Serve as a function‑wide subject matter expert in one or more areas of focus.
- Actively contribute to the engineering community as an advocate of firmwide frameworks, tools, and practices of the Software Development Life Cycle.
- Influence peers and project decision‑makers to consider the use and application of leading‑edge technologies.
Required Qualifications, Capabilities, And Skills
- Design and implementation of front‑office systems for quant trading.
- Hands‑on practical experience delivering system design, application development, testing, and operational stability.
- Strong expertise in Python. Comfortable with scientific & dataset libraries such as pandas, numpy.
- Experience with KDB/Q.
- Knowledge of data pipelines, market data processing and backtesting workflows.
- Advanced knowledge of software applications and technical processes with considerable in‑depth knowledge in one or more technical disciplines.
- Ability to tackle design and functionality problems independently with little to no oversight.
- Proficiency in automation and continuous delivery methods.
- In‑depth knowledge of the financial services industry and their IT systems.
- Academic experience in Computer Science, Computer Engineering, Mathematics, or a related technical field.
- Knowledge of machine learning, statistical techniques and related libraries.
Preferred Qualifications, Skills And Capabilities
- Strong knowledge and experience in FIX, Market Data, Analytics, OMS, and equities trading in global markets are assets.
- Additional knowledge of Java / C++ is a strong plus.
- Practical cloud native experience is a plus.
- Practical cloud experience is a plus.
Python Quant Data Engineer - Systematic Trading Technology in London employer: J.P. Morgan
At J.P. Morgan, we pride ourselves on being a premier employer, offering a dynamic work environment that fosters innovation and collaboration within our technology teams. As a Python Quant Data Engineer, you will not only contribute to cutting-edge projects in systematic trading but also benefit from extensive professional development opportunities and a culture that values diversity and inclusion. Our commitment to employee growth, coupled with the chance to work alongside industry leaders in a global financial powerhouse, makes this an exceptional place to advance your career.
StudySmarter Expert Advice🤫
We think this is how you could land Python Quant Data Engineer - Systematic Trading Technology in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those at JPMorgan Chase. A friendly chat can open doors and give you insights that job descriptions just can't.
✨Tip Number 2
Show off your skills! If you've got a portfolio or GitHub with projects related to Python, data pipelines, or trading tech, make sure to highlight them. It’s a great way to demonstrate your expertise beyond the CV.
✨Tip Number 3
Prepare for the interview by brushing up on your problem-solving skills. Expect technical questions that test your knowledge of Python and data processing. Practice coding challenges to keep your skills sharp!
✨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 serious about joining the team at JPMorgan Chase.
We think you need these skills to ace Python Quant Data Engineer - Systematic Trading Technology in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Python Quant Data Engineer role. Highlight your experience with data pipelines, Python, and any relevant technologies mentioned in the job description. We want to see how your skills align with what we're looking for!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about systematic trading technology and how your background makes you a great fit for our team. Keep it concise but impactful – we love a good story!
Showcase Your Projects:If you've worked on any relevant projects, whether in a professional or academic setting, make sure to mention them. We’re interested in seeing how you've applied your skills in real-world scenarios, especially those involving Python and data analytics.
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands. Plus, it shows us that you’re genuinely interested in joining our team at StudySmarter!
How to prepare for a job interview at J.P. Morgan
✨Know Your Tech Inside Out
Make sure you brush up on your Python skills and get comfortable with libraries like pandas and numpy. Be ready to discuss your experience with data pipelines and how you've tackled design problems in the past.
✨Showcase Your Problem-Solving Skills
Prepare to share specific examples of challenges you've faced in previous roles, especially related to quantitative trading or data analytics. Highlight your thought process and the methodologies you used to overcome these obstacles.
✨Understand the Business Context
Familiarise yourself with the financial services industry and J.P. Morgan's role within it. Being able to connect your technical expertise to the business objectives will show that you understand the bigger picture.
✨Engage with the Team Dynamics
Since you'll be part of an agile technology team, be prepared to discuss how you collaborate with others. Share your experiences working with cross-functional teams and how you’ve contributed to a positive team environment.
