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- Tasks: Lead and shape the data engineering platform for a cutting-edge fintech.
- Company: Fast-growing UK fintech scale-up revolutionising debt capital markets.
- Benefits: Competitive salary, equity, hybrid work, flexible hours, and work abroad opportunities.
- Why this job: Make a real impact in a dynamic environment with innovative technology.
- Qualifications: Strong Python and SQL skills, experience with data platforms and orchestration tools.
- Other info: Join a vibrant team in a rapidly expanding company with excellent growth potential.
The predicted salary is between 72000 - 108000 £ per year.
A well-funded UK fintech scale-up is building an AI-native SaaS platform used by investment banks, asset managers and hedge funds to make real-time decisions in debt capital markets. Following a recent Series B and a period of rapid growth, they’re investing in their data platform to improve reliability, scale and commercial impact. This role sits at the core of the product, with clear ownership and the opportunity to shape how data engineering supports both internal teams and customer-facing features.
The Role
- Own the technical direction and delivery of the data engineering platform across ingestion, orchestration and warehousing.
- Remain hands-on in the code while leading a small data engineering team as it grows.
- Improve platform reliability, observability and data quality to reduce firefighting.
- Define and deliver a clear, pragmatic roadmap focused on scalability and operational excellence.
- Build and evolve customer-facing APIs, feeds and enrichment pipelines as product capabilities.
- Work closely with analytics engineers, analysts and product teams to turn platform work into tangible outcomes.
What You’ll Bring
- Strong hands-on experience owning and operating production data platforms end to end.
- Advanced Python skills and solid SQL fundamentals.
- Experience with modern orchestration tools (Dagster preferred, Airflow or similar acceptable).
- Cloud-native background with AWS or GCP (exposure to both is a plus).
- Comfort working in scale-up environments where structure is still being built.
- Some people leadership experience, whether through line management, tech lead responsibility or mentoring.
- Nice-to-haves include exposure to DBT, data ingestion tooling, or data products and APIs.
What’s On Offer
- Competitive Base Salary plus equity (c.20%, vesting over four years).
- Hybrid working with 1–2 days per week in a London office near Fenchurch Street.
- Flexible working hours with a strong focus on sustainable work-life balance.
- Up to three months per year working abroad.
- A growing data and engineering function within a ~400-person, Series B-backed business.
Head of Data Engineering employer: Wave Talent
Contact Detail:
Wave Talent Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Head of Data Engineering
✨Tip Number 1
Network like a pro! Reach out to folks in the fintech space, especially those who work with data engineering. A casual chat can lead to opportunities that aren’t even advertised yet.
✨Tip Number 2
Show off your skills! If you’ve got a GitHub or portfolio showcasing your data projects, make sure to share it during interviews. It’s a great way to demonstrate your hands-on experience and technical chops.
✨Tip Number 3
Prepare for the technical interview! Brush up on your Python and SQL skills, and be ready to discuss your experience with orchestration tools like Dagster or Airflow. We want to see how you think through problems!
✨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 Head of Data Engineering
Some tips for your application 🫡
Tailor Your CV: Make sure your CV speaks directly to the role of Head of Data Engineering. Highlight your hands-on experience with data platforms and any leadership roles you've had. We want to see how your skills align with our needs!
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 AI-native SaaS platform. Let us know why you're excited about this opportunity and how you can help shape our data strategy.
Showcase Relevant Projects: If you've worked on projects that involved modern orchestration tools or cloud-native environments, make sure to include them. We love seeing real-world examples of your work, especially if they relate to improving platform reliability and scalability.
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 Wave Talent
✨Know Your Tech Inside Out
Make sure you’re well-versed in the technical skills listed in the job description, especially Python and SQL. Brush up on your experience with orchestration tools like Dagster or Airflow, and be ready to discuss how you've used them in past projects.
✨Showcase Your Leadership Skills
Even if you haven’t held a formal leadership position, think of examples where you’ve mentored others or taken the lead on a project. Be prepared to share how you can guide a growing team while remaining hands-on with the code.
✨Understand the Business Context
Familiarise yourself with the fintech landscape and how data engineering plays a role in decision-making for investment banks and asset managers. This will help you articulate how your work can directly impact the company’s goals.
✨Prepare Questions That Matter
Think of insightful questions to ask during the interview that show your interest in the role and the company. Inquire about their current data challenges, the team dynamics, or how they envision the data platform evolving in the future.
