At a Glance
- Tasks: Build a cutting-edge data platform that connects and simplifies complex data systems.
- Company: Fast-growing data intelligence startup in London with strong venture backing.
- Benefits: Competitive salary, relocation support, and a dynamic work environment.
- Other info: Join a founder-led team with minimal bureaucracy and a focus on innovation.
- Why this job: Shape the future of data intelligence and make a real impact on businesses.
- Qualifications: Experience in building data platforms, strong Python skills, and a pragmatic mindset.
The predicted salary is between 59400 - 72600 £ per year.
We’re a well-funded, fast-growing data intelligence startup based in London backed by leading venture investors.
The problem Every growing company eventually reaches the same point: its data is everywhere. Customer information lives in one system. Revenue data sits in another. Product activity, operations and finance each tell a different part of the story. Answering a seemingly simple question often means searching through dashboards, writing queries or waiting for someone to bring the numbers together.
We’re building a better way. We’re building a data intelligence platform for a world in which AI agents, not just people, need to understand and use business information. Our platform connects fragmented data across an organisation, identifies what is happening in real time and explains the factors driving change. It gives agents the context they need to provide reliable answers and take meaningful action.
Our ambition is to move beyond software that waits for someone to ask a question. We want important insights to surface automatically, reach the right person or agent at the right moment, and initiate the appropriate next step. We already have growing customers. Their expanding needs are creating increasingly complex technical challenges and an opportunity to define how the next generation of intelligent systems works with enterprise data.
Now we’re looking for someone to help us build the foundation beneath it all. This is where you come in. We’re looking for an exceptional Founding Data Platform Engineer who has built serious data infrastructure before and wants to do it again, this time with the opportunity to shape the platform from an early stage.
You’ll encounter databases containing hundreds of tables, inconsistent definitions, changing schemas and information spread across tools that were never designed to work together. Your challenge will be to turn that complexity into a platform that is reliable, secure and simple to build upon. You won’t be maintaining a finished architecture. You’ll help decide what that architecture becomes.
Working with the founders, you’ll influence our company's technical direction, engineering standards and approach to some of the hardest problems at the intersection of data and AI.
What you’ll build
- Design and scale the core data platform
- Connect databases, warehouses and third-party business systems
- Build reliable ingestion and integration infrastructure
- Reconcile and unify data from multiple, heterogeneous sources
- Develop flexible ways to model and interpret unfamiliar data
- Shape the semantic models and ontologies that give business data consistent meaning
- Design reliable, observable orchestration for complex data workflows
- Establish strong foundations for data quality, lineage and observability
- Embed permissions, governance and security into the platform from the beginning
- Build infrastructure that intelligent, autonomous software agents can use reliably
Some problems will require careful, long-term architectural thinking. Others will need a pragmatic solution shipped by the end of the week. Knowing which is which will be an important part of the role.
Who we’re looking for
We’re looking for a Founding Data Platform Engineer with deep experience building complex data systems. You’ll likely bring:
- Experience building production-grade data platforms or infrastructure
- Strong software engineering and system-design fundamentals
- High proficiency in Python or another relevant programming language
- A deep understanding of data pipelines, databases and warehouses
- Experience reconciling data from multiple, heterogeneous sources
- Hands-on experience with orchestration and transformation tools such as Airflow, Dagster or dbt
- Familiarity with columnar data systems such as ClickHouse or DuckDB
- Experience with distributed systems and third-party integrations
- A pragmatic mindset and a strong bias towards shipping
- Experience with semantic models, ontologies or knowledge graphs would be a bonus.
You don’t need to meet all the requirements. We care more about what you’ve built, how you think and the level of responsibility you’re ready to take on.
The role is based in London but we will be happy to sponsor visa and support relocation if you need it.
Why this role
We’ve already attracted an exciting group of customers. Now we want to exceed their expectations and build the next stage of the platform alongside them and you. You’ll join a founder-led, fast-paced environment with minimal bureaucracy. You’ll have the freedom, responsibility and support to turn ambitious ideas into working products. You’ll work closely with customers, see the impact of what you build and have a genuine voice in the direction of both the platform and the company.
If we succeed, the infrastructure you help create won’t simply organise business data. It will become the foundation intelligent software relies on to understand organisations and act on their behalf.
Founding Data Platform Engineer employer: Stealth Startup
Join a forward-thinking company that values creativity and innovation, where your design work will play a crucial role in transforming how people perceive their finances. With a flexible remote working environment and the opportunity for ongoing engagement, you'll be part of a supportive culture that encourages personal growth and collaboration. This is not just a job; it's a chance to make a meaningful impact while developing your skills alongside a passionate team dedicated to reshaping financial experiences.
StudySmarter Expert Advice🤫
We think this is how you could land Founding Data Platform 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 Stealth Startup!
✨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 Founding Data Platform Engineer at Stealth Startup.
✨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 Stealth Startup.
✨Apply Directly through Our Website
When you find a suitable opening like Founding Data Platform Engineer at Stealth Startup, 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 Founding Data Platform 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 Stealth Startup, 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 Stealth Startup. 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 Stealth Startup
✨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 Stealth Startup!
✨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.
