At a Glance
- Tasks: Lead the design and build of data pipelines for our innovative AI product.
- Company: Exciting AI startup in London with strong backing and growth potential.
- Benefits: Competitive salary, equity options, and direct access to founders.
- Other info: Join a dynamic team in a market ready for disruption.
- Why this job: Be the first data hire and shape the future of our AI platform.
- Qualifications: 7-10 years in data engineering with strong Python skills and architecture experience.
The predicted salary is between 130000 - 130000 £ per year.
Lead Data Engineer — AI Startup, London | £130k+ | Equity | London | 4 days onsite
We're an early-stage, well-backed AI startup building an automation platform for a large, traditionally slow-moving UK industry.
Live with pilot customers, strong early traction, scaling hard toward revenue this year.
We're hiring our first Lead Data Engineer.
You'll own the data architecture from the ground up: real-time pipelines, analytics infra, and the vector/ML data workflows that power our AI product.
This isn't maintaining someone else's system, you're building it.
- What you'll be doing
- Architecting and building the data pipelines and infrastructure behind our AI product
- Designing ingestion, transformation and storage for both operational and AI workloads
- Building and optimising vector search and ML data pipelines
- Setting the data standards, tooling and hiring bar as the first data hire
- Working directly with the founders, not three layers removed from decisions
- What you'll bring
- 7-10 years in data engineering, with real ownership of architecture decisions, not just execution
- Strong Python, plus experience with tools like Spark, Airflow, Kafka
- Comfortable across relational (Postgres), No SQL, and vector databases (Qdrant, Milvus, pgvector, or similar)
- A background that includes time at a larger, more established tech company, ideally followed by a move into an early-stage or high-growth startup
- You like building things from nothing more than you like maintaining what already exists
- Why this one's worth a look
- Genuinely the first data hire, no legacy mess to untangle
- Direct access to founders and real influence over the roadmap
- Meaningful equity in a company backed by serious investors
- A market that's ripe for disruption and a product that's already landing with customers
- #J-18808-Ljbffr
Lead Data Engineer employer: trg.
As a Lead Data Engineer at our innovative AI startup in London, you'll be at the forefront of building cutting-edge data architecture from scratch, with direct access to the founders and significant influence over the product roadmap. We foster a dynamic work culture that values creativity and ownership, offering meaningful equity and the opportunity to shape the future of a disruptive technology in a rapidly evolving market. Join us for a rewarding career where your contributions will directly impact our success and growth.
StudySmarter Expert Advice🤫
We think this is how you could land Lead Data Engineer
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like trg.!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Lead Data Engineer at trg..
✨Leverage Professional Networks
Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like trg..
✨Apply Directly through Our Website
When you find a suitable opening like Lead Data Engineer at trg., make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace Lead Data Engineer
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at trg., your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at trg.. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at trg.
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at trg.!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
