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 in London 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 a culture that champions high autonomy and execution, you'll have the opportunity to lead a talented data engineering team while directly impacting the modernization of a $141 trillion asset class. Enjoy competitive compensation, equity options, and the chance to work closely with visionary founders in a fast-paced, growth-oriented 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 in London
✨Tip Number 1
Network like a pro! Reach out to your connections in the industry, especially those who work at companies you're interested in. A friendly chat can lead to referrals, which are often the best way to get your foot in the door.
✨Tip Number 2
Show off your skills! Create a portfolio or GitHub repository showcasing your data engineering projects. This gives potential employers a tangible look at what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for interviews by practising common technical questions and scenarios related to data engineering. We recommend doing mock interviews with friends or using online platforms to boost your confidence.
✨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 take that extra step to connect with us directly.
We think you need these skills to ace Data Engineering Lead (~£115k + Equity) at Series B AI-powered debt capital markets platform in London
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 specific projects that demonstrate your ability to build and scale production data platforms. We love seeing real-world examples of your work, especially if they relate to cloud-native environments or Infrastructure-as-Code.
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 updates from us!
How to prepare for a job interview at Jack & Jill
✨Know Your Tech Inside Out
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. Be ready to discuss your hands-on experience with these tools and how you've used them to build and scale data platforms.
✨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 approach to fostering high performance and collaboration.
✨Understand the Business Impact
This role is all about transforming the debt capital market with data. Research the company’s mission and be prepared to discuss how your technical skills can directly contribute to their goals, especially in modernising their data infrastructure.
✨Prepare for Scenario-Based Questions
Expect questions that assess your problem-solving abilities in real-world scenarios. Think about challenges you've faced in previous roles, particularly around data ingestion and orchestration, and how you overcame them. This will show your practical understanding of the role.
