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- Tasks: Build and scale modern data pipelines while supporting AI-driven products.
- Company: Exciting AI startup transforming a major UK industry.
- Benefits: Competitive salary up to £140k, equity, and a strong engineering culture.
- Why this job: Be the first data hire and make a significant impact from day one.
- Qualifications: 7+ years in Data/Backend Engineering with strong Python skills.
- Other info: Join a fast-paced environment with excellent growth opportunities.
The predicted salary is between 84000 - 140000 £ per year.
Tech Stack: Python | Spark | Kafka | Airflow | Vector DBs
Location: London - office based
Salary: Up to £140k + equity
We’re partnering with a well-funded AI startup building a category-defining platform within a major UK industry undergoing rapid transformation. This is a first data hire and a genuinely high-impact role, owning and building the entire data infrastructure from the ground up. You’ll work closely with AI and engineering teams to design scalable data pipelines, support machine learning systems, and enable real-time, intelligent decision-making across the platform.
What you’ll be doing:
- Building and scaling modern data pipelines (batch + real-time)
- Designing data architecture across relational, NoSQL, and vector databases
- Supporting ML workflows and AI-driven products
- Driving performance, scalability, and data reliability
- Influencing technical strategy in a fast-growing environment
What we’re looking for:
- 7+ years in Data / Backend Engineering
- Strong Python and distributed systems experience
- Hands-on with modern data tooling (Spark, Airflow, Kafka, etc.)
- Experience with relational + NoSQL databases (vector DBs a big plus)
- Comfortable in a fast-paced, early-stage environment
High ownership, strong engineering culture, and meaningful equity on offer.
Apply or message me directly for more details.
Lead Data Engineer in London employer: JGA Recruitment Group | B CorpTM
Contact Detail:
JGA Recruitment Group | B CorpTM Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Lead Data Engineer in London
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with potential colleagues 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 showcasing your projects, especially those involving Python, Spark, and Kafka. This will give you an edge and demonstrate your hands-on experience to potential employers.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. Practice common data engineering scenarios and be ready to discuss how you've tackled challenges in past roles.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you're genuinely interested in joining our team and contributing to our exciting projects.
We think you need these skills to ace Lead Data Engineer in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Lead Data Engineer role. Highlight your experience with Python, Spark, and other relevant tech. We want to see how your skills match what we're looking for!
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 startup. Keep it concise but impactful – we love a good story!
Showcase Your Projects: If you've worked on any cool data projects, don’t hold back! Include links or descriptions of your work that demonstrate your ability to build scalable data pipelines and support ML workflows. We’re keen to see your hands-on experience!
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for this exciting opportunity. Let’s get started on this journey together!
How to prepare for a job interview at JGA Recruitment Group | B CorpTM
✨Know Your Tech Stack Inside Out
Make sure you’re well-versed in Python, Spark, Kafka, and Airflow. Brush up on how these technologies work together to build scalable data pipelines. Be ready to discuss your hands-on experience with them and any projects where you've implemented these tools.
✨Showcase Your Problem-Solving Skills
Prepare to share specific examples of challenges you've faced in data engineering. Think about how you’ve designed data architecture or improved performance and reliability in past roles. This will demonstrate your ability to influence technical strategy in a fast-paced environment.
✨Understand the Business Context
Research the AI startup and its industry. Understand their goals and how your role as a Lead Data Engineer can impact their success. This knowledge will help you tailor your answers and show that you’re genuinely interested in contributing to their mission.
✨Ask Insightful Questions
Prepare thoughtful questions about the company’s data strategy, team dynamics, and future projects. This not only shows your enthusiasm but also helps you gauge if the company culture aligns with your values and work style.