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For Companies At a Glance
- Tasks: Lead engineering teams to build and scale innovative data-driven platforms.
- Company: Fast-growing tech company focused on cutting-edge technology.
- Benefits: Competitive salary, flexible work options, and opportunities for professional growth.
- Why this job: Make a significant impact by driving technical excellence in a dynamic environment.
- Qualifications: Proven leadership in engineering with experience in distributed systems and machine learning.
- Other info: Join a culture of collaboration and high performance with excellent career advancement.
The predicted salary is between 43200 - 72000 ÂŁ per year.
A fast‑growing technology company is seeking a Head of Engineering with deep experience building and scaling complex, data‑driven platforms. This role requires someone who can lead multi‑disciplinary teams, improve engineering execution, and drive technical excellence across high‑scale distributed systems and machine‑learning environments.
Required Experience
- Leadership of engineering organisations of 20 or more across multiple disciplines, including backend, web, data, ML, QA, and DevOps.
- Proven track record designing, scaling, and maintaining distributed systems and high‑volume data pipelines.
- Strong background in cloud‑native architectures and modern data stacks such as Spark or Databricks.
- Experience working closely with Data Science teams, including delivering production‑grade ML models and pipelines.
- Solid understanding of modern frontend engineering practices (e.g., TypeScript, React) to guide cross‑functional technical decisions.
- Robust DevOps knowledge, including CI/CD pipelines, container orchestration, monitoring, reliability engineering, and cloud infrastructure management (AWS preferred).
- Demonstrated ability to balance delivery speed with long‑term technical quality, reliability, and maintainability.
- Experience hiring, mentoring, and developing engineering leaders and high‑performing teams.
Role Overview
You will own engineering execution for a platform that processes large datasets, supports distributed computation, and integrates machine‑learning capabilities at scale. The engineering organisation already uses AI‑assisted development, and you will refine these practices, improve delivery predictability, and strengthen the technical foundation for long‑term growth.
Responsibilities
- Lead the engineering roadmap and technical execution across all product and platform teams.
- Guide architectural decisions in data engineering, ML, and web application development.
- Implement engineering KPIs to improve delivery speed, quality, and reliability.
- Develop a strong engineering culture centred on ownership, collaboration, and high performance.
- Partner with Product, Data Science, and DevOps to deliver high‑quality, scalable solutions.
- Manage engineering budgets, tooling, and cloud infrastructure costs.
Preferred
- Experience in search, advertising technology, or competitive intelligence.
- Familiarity with ML lifecycle tooling and agentic coding approaches.
Please send me a copy of your CV if you meet all of the above.
Head of Engineering in London employer: Jefferson Frank
Contact Detail:
Jefferson Frank Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Head of Engineering in London
✨Tip Number 1
Network like a pro! Reach out to your connections in the tech industry, especially those who work in engineering roles. A personal introduction can make all the difference when you're aiming for that Head of Engineering position.
✨Tip Number 2
Showcase your expertise! Prepare a portfolio or case studies that highlight your experience with distributed systems and machine learning. This will help you stand out during interviews and demonstrate your technical prowess.
✨Tip Number 3
Practice makes perfect! Conduct mock interviews with friends or mentors to refine your responses, especially around leadership and technical challenges. This will boost your confidence and help you articulate your vision for engineering execution.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace Head of Engineering in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the specific skills and experiences mentioned in the job description. Highlight your leadership experience and any relevant projects that showcase your ability to manage multi-disciplinary teams and scale complex systems.
Showcase Technical Expertise: Don’t shy away from detailing your technical skills, especially in cloud-native architectures and data engineering. Mention any hands-on experience with tools like Spark or Databricks, as well as your familiarity with modern frontend practices like TypeScript and React.
Highlight Leadership Experience: Since this role is all about leading teams, make sure to emphasise your experience in hiring, mentoring, and developing engineering leaders. Share examples of how you've built high-performing teams and fostered a strong engineering culture.
Apply Through Our Website: We encourage you to apply directly through our website for a smoother application process. It’s the best way for us to receive your application and get to know you better!
How to prepare for a job interview at Jefferson Frank
✨Know Your Tech Inside Out
Make sure you’re well-versed in the technologies mentioned in the job description, like cloud-native architectures and data stacks. Brush up on your knowledge of distributed systems and machine learning environments, as you’ll likely be asked to discuss your experience with these during the interview.
✨Showcase Your Leadership Skills
Prepare examples that highlight your leadership experience, especially managing teams of 20 or more across various disciplines. Be ready to discuss how you've mentored engineering leaders and fostered a high-performance culture in your previous roles.
✨Demonstrate Cross-Functional Collaboration
Since this role involves working closely with Product, Data Science, and DevOps teams, think of specific instances where you’ve successfully collaborated across functions. Highlight how you’ve guided architectural decisions and improved engineering execution through teamwork.
✨Prepare for Scenario-Based Questions
Expect scenario-based questions that assess your problem-solving skills and ability to balance delivery speed with technical quality. Think about challenges you’ve faced in past projects and how you overcame them, particularly in high-volume data pipeline scenarios.