At a Glance
- Tasks: Build and support cutting-edge data pipelines for systematic trading technology.
- Company: Join JPMorgan Chase's innovative tech team in a dynamic environment.
- Benefits: Competitive salary, health benefits, and opportunities for professional growth.
- Other info: Collaborative culture with excellent career advancement opportunities.
- 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 employer: Jpmorgan Chase & Co.
At JPMorgan Chase, we pride ourselves on being an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration within our agile technology teams. As a Python Quant Data Engineer, you will not only contribute to cutting-edge technology solutions for systematic trading but also benefit from extensive professional development opportunities and a supportive environment that values your expertise and growth. Located in a vibrant financial hub, our team is dedicated to pushing the boundaries of technology while ensuring a secure and stable work atmosphere, making it an ideal place for those seeking meaningful and rewarding careers.
StudySmarter Expert Advice🤫
We think this is how you could land Python Quant Data Engineer - Systematic Trading Technology
✨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 in quant trading. Building relationships can open doors that job applications alone can't.
✨Show Off Your Skills
Don’t just talk about your experience; demonstrate it! Create a portfolio showcasing your Python projects, especially those related to data pipelines or quantitative research. This will give potential employers a taste of what you can bring to the table.
✨Ace the Interview
Prepare for technical interviews by brushing up on your Python skills and understanding of data processing. Practice common coding challenges and be ready to discuss your problem-solving approach. Confidence is key!
✨Apply Through Our Website
Make sure to apply directly through our website! It’s the best way to ensure your application gets seen by the right people. 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
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the role of Python Quant Data Engineer. Highlight your experience with Python, data pipelines, 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. Don’t forget to mention specific technologies or methodologies you’ve worked with.
Showcase Your Technical Skills:In your application, be sure to highlight your technical expertise, especially in Python and any scientific libraries like pandas and numpy. Mention any hands-on experience you've had with data ingestion, cleaning, and backfilling to demonstrate your practical knowledge.
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 keep track of your application and ensure it reaches the right people in our tech 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 skills and get familiar with libraries like pandas and numpy. Be ready to discuss how you've used these tools in past projects, especially in relation to data pipelines and quantitative trading.
✨Understand the Business Context
Get a good grasp of the financial services industry and how technology plays a role in systematic trading. Being able to connect your technical expertise to real-world applications will impress the interviewers.
✨Showcase Problem-Solving Skills
Prepare to discuss specific challenges you've faced in previous roles and how you tackled them. Highlight your ability to work independently and your experience with automation and continuous delivery methods.
✨Engage with the Team's Goals
Research the Equities Trading Data & Analytics technology team and understand their objectives. Be ready to share ideas on how you can contribute to building robust tools and frameworks that support their goals.
