At a Glance
- Tasks: Build and support data pipelines for cutting-edge trading technology.
- Company: Join JPMorgan Chase's innovative tech team in systematic trading.
- Benefits: Competitive salary, health benefits, and opportunities for professional growth.
- Other info: Dynamic environment with excellent career advancement opportunities.
- Why this job: Make a real impact in finance with your tech skills and creativity.
- Qualifications: Strong Python skills and experience in quantitative trading systems.
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: JPMorganChase
At JPMorgan Chase, we pride ourselves on being an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration. As a Python Quant Data Engineer in our Equities Trading Data & Analytics technology team, you will have access to cutting-edge technology and the opportunity for significant professional growth, all while working in a supportive environment that values your contributions and expertise. Our commitment to employee development, coupled with the chance to make a tangible impact in the financial services industry, makes this role not just a job, but a meaningful career path.
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 that a CV just can't.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your Python projects, especially those related to data pipelines or quantitative research. This will give you an edge when discussing your experience.
✨Tip Number 3
Prepare for technical interviews by brushing up on your problem-solving skills. Practice coding challenges and be ready to discuss your thought process. We all know how crucial it is to demonstrate your expertise!
✨Tip Number 4
Don't forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing candidates who are proactive about their job search.
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. 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 perfect fit for our team. Keep it engaging and personal!
Showcase Your Projects:If you've worked on any relevant projects, make sure to mention them! Whether it's building data pipelines or developing trading analytics libraries, we love to see practical examples of your work and problem-solving skills.
Apply Through Our Website:We encourage you to apply through our website for the best chance of getting noticed. It helps us keep track of applications and ensures you’re considered for the role. Plus, it’s super easy!
How to prepare for a job interview at JPMorganChase
✨Know Your Python Inside Out
Make sure you brush up on your Python skills, especially with libraries like pandas and numpy. Be ready to discuss how you've used these tools in past projects, as well as any challenges you've faced and how you overcame them.
✨Understand the Trading Landscape
Familiarise yourself with the basics of systematic trading and the financial services industry. Being able to speak knowledgeably about market data processing and backtesting workflows will show that you're not just a techie but also understand the business side of things.
✨Prepare for Technical Questions
Expect to tackle some technical questions or even coding challenges during the interview. Practice common algorithms and data structures, and be prepared to explain your thought process clearly. This will demonstrate your problem-solving skills and technical expertise.
✨Showcase Your Collaboration Skills
Since you'll be working closely with research and trading teams, highlight any experience you have in cross-functional collaboration. Share examples of how you've successfully onboarded new datasets or built tools that improved team efficiency.
