At a Glance
- Tasks: Lead innovative projects in financial analytics and AI data integration.
- Company: Join a forward-thinking company shaping the future of finance.
- Benefits: Career growth, collaboration, and a culture of innovation await you.
- Other info: Mentorship opportunities and a focus on diversity and inclusion.
- Why this job: Make a real impact with your ideas and leadership in a dynamic environment.
- Qualifications: Experience in software engineering, especially in fast-paced financial settings.
The predicted salary is between 60000 - 80000 £ per year.
Join us to shape the future of financial analytics and technology. You will lead impactful projects that drive advanced data engineering and AI solutions across global teams. We offer opportunities for career growth, collaboration, and technical excellence. Your expertise will help us deliver mission-critical systems and foster a culture of innovation. Be part of a team where your ideas and leadership make a difference.
As a Lead Data Engineering & AI Technical Initiatives in the Global Analytics team, you will guide technical direction and drive innovation in real-time data processing. You will collaborate with research and trading teams to deliver advanced analytics capabilities and support global business needs. Your role will focus on building robust tools, mentoring team members, and influencing product design. You will help shape our technical standards and foster a diverse, inclusive, and collaborative environment.
Job Responsibilities:
- Lead technical initiatives across global analytics teams, providing guidance and direction in a high-velocity environment.
- Design, build, and optimize real-time data processing pipelines and applications to ensure reliability and performance.
- Leverage AI technologies to enhance data engineering workflows and automate SDLC processes.
- Collaborate with research and trading teams to onboard new datasets efficiently and consistently.
- Drive team adoption of enterprise-authorized AI-assisted engineering practices within the work environment to improve code quality, delivery speed, and operational outcomes.
- Apply knowledge of tools within the Software Development Life Cycle toolchain to improve the value realized by automation.
- Build and support robust tools and frameworks for quantitative research and production trading.
- Mentor and develop team members, manage book of work, and drive continuous improvement in SDLC, testing, and coding standards.
- Influence product design, application functionality, and technical operations to meet evolving business demands.
- Serve as a subject matter expert in Python, KDB/Q, data engineering, and AI.
- Champion diversity, inclusion, and collaboration within global teams.
Required Qualifications, Capabilities, and Skills:
- Applied experience in software engineering, preferably in large-scale, fast-paced financial environments.
- Hands-on experience delivering system design, application development, testing, and operational stability for analytics-driven teams.
- Expertise in Python, KDB, or C++ for real-time data processing, application development, or data engineering.
- Working knowledge of AI technologies to support data engineering, analytics, or SDLC automation.
- Demonstrated experience leading effective use of approved AI-assisted software development tools.
- Strong understanding of responsible AI use in engineering workflows.
- Proficiency in automation and continuous delivery methods; advanced understanding of agile methodologies.
- Experience leading and mentoring teams in a global, collaborative environment.
- Ability to tackle complex design and functionality problems independently.
- 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.
- Knowledge and experience in FIX, Market Data, Analytics, OMS, and equities trading.
Lead Software Engineer - Python and kdb+ / AI data integration, Alt Data & Data Ingestion in London employer: Jpmorgan Chase & Co.
Join a forward-thinking company that prioritises innovation and collaboration in the financial analytics sector. As a Lead Software Engineer, you will thrive in a dynamic work culture that values your expertise and encourages professional growth through mentorship and impactful projects. With a commitment to diversity and inclusion, this role offers a unique opportunity to shape cutting-edge AI solutions while working alongside global teams dedicated to excellence.
StudySmarter Expert Advice🤫
We think this is how you could land Lead Software Engineer - Python and kdb+ / AI data integration, Alt Data & Data Ingestion in London
✨Join Local Tech Meetups
Get out there and mingle with fellow developers by joining local tech meetups. It’s a fantastic way to meet people who might be working at Jpmorgan Chase & Co. or know someone who does. Plus, you can pick up some trendy tech skills and trends while you're at it!
✨Contribute to Open Source Projects
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✨Tap into Online Developer Communities
Don’t underestimate the power of online developer communities like GitHub, Stack Overflow, and even Reddit. Participate in discussions, share your projects, and build your visibility. We can often find opportunities through these channels that can lead to a full-time gig at companies like Jpmorgan Chase & Co..
✨Explore Job Boards Specifically for Tech Roles
Keep your eyes peeled on job boards that focus on tech roles. Sites like TechCareers or Stack Overflow Jobs can often have listings for companies like Jpmorgan Chase & Co. that might not show up on broader job sites. Make it a habit to check these regularly, and don’t hesitate to apply directly through our website!
We think you need these skills to ace Lead Software Engineer - Python and kdb+ / AI data integration, Alt Data & Data Ingestion in London
Some tips for your application 🫡
Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.
Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at Jpmorgan Chase & Co..
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at Jpmorgan Chase & Co. and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!
Be clear and concise:When it comes to writing your CV and cover letter, clarity is key. Avoid jargon that could confuse us and stick to simple, direct language. Highlight your achievements with quantifiable results where possible, and keep everything easy to read. A well-organised application goes a long way!
How to prepare for a job interview at Jpmorgan Chase & Co.
✨Brush Up on Your Coding Skills
For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.
✨Know Your Tools and Frameworks
Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If Jpmorgan Chase & Co. uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.
✨Showcase Your Projects
Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.
✨Prepare for Behavioural Questions
While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.
