At a Glance
- Tasks: Lead the design and implementation of data architecture for an innovative AI platform.
- Company: Exciting pre-Series-A AI startup transforming property management.
- Benefits: Competitive salary, equity options, and flexible working arrangements.
- Other info: Join a dynamic team with opportunities for career advancement and direct impact.
- Why this job: Be the first senior data hire and shape the future of data infrastructure.
- Qualifications: 7+ years in data engineering with strong Python and vector database experience.
The predicted salary is between 85000 - 85000 £ per year.
Lead Data Engineer | Python, Kafka, Vector Databases | First Senior Data Hire at a Pre-Series-A AI Platform
- Salary: from c. £85k, plus early-stage equity
- Location: Victoria, central London. 4 days a week in the office, Wednesdays from home
- Right to work: existing UK right to work, no sponsorship
- Also hiring: a Senior Data Engineer on the same team, one rung down
I’m working with an AI startup in London that’s automating the admin out of property management.
Unglamorous problem in a very large market, which is usually where the money turns out to be, and they’re already live with pilot customers managing thousands of units.
You’ll be their first senior data hire.
The architecture is close to a blank slate, so you’re the one deciding what it looks like: Python, Postgres, Kafka and vector databases doing the retrieval behind a product people use every day.
Fair warning on the vector database side, that’s the bit they’re strictest on and they’ve turned good engineers down for being light there. Lead with it.
Four days a week in the office in Victoria with Wednesdays from home. It’s a dozen or so engineers, and they want everyone in the room while it’s this early.
- What They’re Looking For (Non-Negotiables)
- Vector databases: Qdrant, Milvus, pgvector or similar, used in a live system. No flex here
- Python: strong and production-grade
- 7+ years in data or backend engineering
- Data pipelines: built and owned at scale
- Postgres (My SQL considered) and No SQL
- Kafka or similar
- Real-time streaming
- UK right to work: no sponsorship on this one, and no flex on it either
- Permanent hire, not a contract engagement
- What You’ll Work With
- Mongo DB
- Spark
- Airflow
- Elasticsearch / Open Search
- Pandas and Polars
- Machine learning (ML) data workflows, alongside the AI and backend engineers
- You’ll own the architecture end to end, tooling and standards included
- Nice to Haves
- AI / ML platform experience
- Event-driven architectures
- Cloud: GCP, AWS or Azure
- Early-stage or high-growth startup experience
- Why Join / Projects
You’ll build the pipelines and infrastructure the whole product runs on: batch and real-time ingestion, transformation, storage, the lot, starting from close to nothing.
Vector search, retrieval and the ML pipelines are yours to design, then make fast as usage climbs.
After that you set the reliability, security and governance standards, hire the people who work to them, and run the function you built.
Flat structure, leads are senior ICs, and you’ll be in the room with the founders and the Head of Engineering when the decisions get made.
There’s a head of data seat at the end of this if you want it.
They’re pre-Series-A with live pilots and a revenue push behind them, so you’re in before the raise rather than after it, which is the point of taking equity in the first place.
- Employee Benefits
- Equity: a meaningful stake, in line with joining as an early senior hire
- One day a week from home, Wednesdays
Then the engineers, the Head of Engineering, and the founders.
The Senior Data Engineer role is worth a word too.
Same team, same stack, same office, one rung down, so you’re building the pipelines alongside the lead instead of defining the architecture yourself.
If you’re five years or so in and this ad reads like a stretch, that’s the one to ask me about.
Same call either way.
Lead Data Engineer | Python, Kafka, Vector Databases | First Senior Data Hire at a Pre-Series-A AI Platform
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Senior/Lead Data Engineer in London employer: Prism Digital
Join a dynamic and innovative AI consultancy in London, where you'll have the opportunity to lead hands-on data projects while working closely with a supportive team. With a flat structure and direct access to leadership, you can expect a collaborative work culture that fosters personal growth and offers a clear path to advancing your career as the company scales. Enjoy a flexible hybrid working model, competitive salary, and performance bonuses that reward your contributions to client success.
StudySmarter Expert Advice🤫
We think this is how you could land Senior/Lead Data Engineer in London
✨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 Prism Digital!
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✨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 Prism Digital.
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We think you need these skills to ace Senior/Lead Data Engineer in London
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 Prism Digital, 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 Prism Digital. 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 Prism Digital
✨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 Prism Digital!
✨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.
