At a Glance
- Tasks: Build and support data pipelines for cutting-edge trading technology.
- Company: Join J.P. Morgan, a global leader in financial services.
- Benefits: Competitive salary, diverse culture, and opportunities for 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 systematic trading.
- 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.
About Us
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.
About The Team
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.
Python Quant Data Engineer - Systematic Trading Technology employer: J.P. Morgan
J.P. Morgan is an exceptional employer, offering a dynamic work environment where innovation and collaboration thrive. As a Python Quant Data Engineer, you will be part of a cutting-edge technology team that values your contributions and provides ample opportunities for professional growth in the fast-paced world of finance. With a strong commitment to diversity and inclusion, J.P. Morgan fosters a supportive culture that empowers employees to excel and make a meaningful impact on global markets.
StudySmarter Expert Advice🤫
We think this is how you could land Python Quant Data Engineer - Systematic Trading Technology
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those at JPMorgan. A friendly chat can open doors that applications alone 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 during interviews.
✨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—it's all about how you tackle problems!
✨Tip Number 4
Don't forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, it shows you're genuinely interested in being part of the team.
We think you need these skills to ace Python Quant Data Engineer - Systematic Trading Technology
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 projects that showcase your skills in quantitative research and trading.
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 at J.P. Morgan.
Showcase Your Technical Skills:Don’t hold back on showcasing your technical expertise! Mention your hands-on experience with libraries like pandas and numpy, and any knowledge of KDB/Q or cloud technologies that could set you apart.
Apply Through Our Website:We encourage you to apply through our website for the best chance of getting noticed. It’s the easiest way for us to see your application and get you into the process!
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 how you've used these tools in past projects, especially in building data pipelines or analytics libraries.
✨Understand the Business Context
Familiarise yourself with the financial services industry and how systematic trading works. Knowing the basics of equities trading and market data processing will help you connect your technical skills to the business needs during the interview.
✨Prepare for Problem-Solving Questions
Expect to tackle design and functionality problems during the interview. Practice explaining your thought process clearly and concisely, as this will demonstrate your ability to work independently and think critically under pressure.
✨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 onboarded new datasets or contributed to team projects, emphasising your role in achieving common goals.
