At a Glance
- Tasks: Lead the evolution of a data platform for the debt capital market.
- Company: Series B AI-powered financial analytics platform backed by top investors.
- Benefits: Competitive salary, equity options, and a dynamic work environment.
- Other info: Join a high-autonomy culture with exceptional growth opportunities.
- Why this job: Make a real impact on modernising the world's largest asset class with AI.
- Qualifications: Experience in building data platforms using Python, SQL, and orchestration tools.
The predicted salary is between 115000 - 115000 € per year.
Company Description: Series B AI-powered financial analytics platform backed by Spark Capital and Highland Europe.
Job Description: Lead the technical evolution of a data platform powering the $141 trillion debt capital market. As a hands-on player/coach, you will own the ingestion, orchestration, and warehousing infrastructure that 9 of the top 10 investment banks rely on. You will industrialize customer-facing data products and scale the engineering team during a period of 400% ARR growth.
Location: London, UK
Why this role is remarkable: Direct ownership of a critical platform at a $50M Series B scale-up where data is the core product, not just a support function. High-impact mission to modernize the world's largest asset class by replacing fragmented, 1980s-era tooling with real-time AI analytics. Exceptional culture of high autonomy and execution, working alongside founders who have scaled the company to support firms with $17 trillion AUM.
What You Will Do:
- Own the end-to-end data engineering operating model, defining ingestion, orchestration, and warehouse foundations across the entire organization.
- Lead the development of commercial-grade APIs and data feeds, implementing SLA-driven operations and clear schema contracts for global institutional clients.
- Mentor and grow a high-performing data engineering team, shifting from 1-2 to ~4 reports while maintaining a 75% hands-on technical focus.
The ideal candidate:
- Proven experience building and scaling production data platforms using Python, SQL, and modern orchestration tools like Dagster or Airflow.
- Strong architectural fluency in cloud-native environments, specifically across AWS and GCP with practical Infrastructure-as-Code experience.
- High-agency leader who has successfully transitioned data infrastructure from early-stage to growth-stage maturity within a fast-paced startup or scale-up environment.
Data Engineering Lead (~£115k + Equity) at Series B AI-powered debt capital markets platform employer: Jack & Jill
Join a dynamic Series B AI-powered financial analytics platform in London, where you will play a pivotal role in transforming the debt capital markets with cutting-edge data solutions. Enjoy a culture that champions high autonomy and execution, alongside founders who have successfully scaled the company, while benefiting from competitive compensation, equity options, and significant opportunities for personal and professional growth in a rapidly expanding environment.
StudySmarter Expert Advice🤫
We think this is how you could land Data Engineering Lead (~£115k + Equity) at Series B AI-powered debt capital markets platform
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with people on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio or GitHub repository showcasing your data engineering projects. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on technical questions and real-world scenarios. Practice explaining your thought process and problem-solving approach, as this is key for roles like Data Engineering Lead.
✨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, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace Data Engineering Lead (~£115k + Equity) at Series B AI-powered debt capital markets platform
Some tips for your application 🫡
Tailor Your CV:Make sure your CV speaks directly to the role of Data Engineering Lead. Highlight your experience with Python, SQL, and orchestration tools like Dagster or Airflow. We want to see how your skills align with our mission to modernise the debt capital market.
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Share your passion for data engineering and how you can contribute to our high-impact mission. Don’t forget to mention your leadership style and how you plan to mentor and grow our team.
Showcase Relevant Projects:Include examples of projects where you've built and scaled production data platforms. We love seeing real-world applications of your skills, especially in cloud-native environments like AWS and GCP. This will help us understand your hands-on experience.
Apply Through Our Website:We encourage you to apply through our website for a smoother application process. It helps us keep track of your application and ensures you don’t miss out on any important updates from us!
How to prepare for a job interview at Jack & Jill
✨Know Your Tech Stack
Make sure you’re well-versed in the technologies mentioned in the job description, like Python, SQL, and orchestration tools such as Dagster or Airflow. Brush up on your cloud-native environments, especially AWS and GCP, so you can confidently discuss your experience and how it aligns with their needs.
✨Showcase Your Leadership Skills
As a Data Engineering Lead, you'll need to demonstrate your ability to mentor and grow a team. Prepare examples of how you've successfully led teams in the past, focusing on your hands-on approach and how you’ve scaled operations in a fast-paced environment.
✨Understand Their Mission
Familiarise yourself with the company’s mission to modernise the debt capital market. Be ready to discuss how your skills can contribute to this high-impact goal and how you can help replace outdated tooling with innovative AI analytics.
✨Prepare Questions
Interviews are a two-way street! Prepare insightful questions about their data platform, the challenges they face, and their vision for the future. This shows your genuine interest in the role and helps you assess if the company culture aligns with your values.
