At a Glance
- Tasks: Design and own the data architecture for a cutting-edge fintech platform.
- Company: Innovative fintech company focused on data-driven solutions.
- Benefits: Hybrid working, European travel, and opportunities to influence technology strategy.
- Other info: Join a fast-growing fintech where your decisions matter.
- Why this job: Shape the future of data architecture and impact customer experiences directly.
- Qualifications: Experience as a Data Architect with strong skills in Snowflake and team leadership.
The predicted salary is between 70000 - 90000 £ per year.
We're partnering with an innovative, product-led fintech that's investing heavily in its data platform and is looking for an experienced Data Architect to help shape the future of its data capability. This is an opportunity to join a business where data sits at the heart of the product. You'll take ownership of the data architecture, lead the data function, and design a modern, scalable platform that enables customers to make smarter, data-driven decisions.
This is far more than a traditional data architecture role. You'll have the autonomy to influence technical strategy, work closely with Product and Engineering, and build a platform that will directly impact the customer experience.
What you'll be doing:
- Designing and owning the overall data architecture and strategy.
- Building a scalable, cloud-native data platform using Snowflake.
- Creating customer-focused data products and capabilities.
- Leading and mentoring the data team.
- Working closely with Product, Engineering and senior stakeholders to shape the data roadmap.
- Establishing best practices around architecture, governance and data quality.
- Driving innovation and ensuring the platform can scale with the business.
What we're looking for:
- Proven experience as a Data Architect or similar senior data leadership role.
- Strong hands-on experience designing and implementing data platforms with Snowflake.
- Background working within a product-led fintech or technology business.
- Experience building customer-facing data products or platforms.
- Strong understanding of modern cloud data architectures.
- Experience leading technical teams and influencing engineering best practice.
- Excellent stakeholder management and communication skills.
What's important:
We're particularly interested in people who have worked in fast-growing, product-focused fintech organisations. This role is not suited to candidates whose experience has been primarily within large, traditional banking environments or enterprise reporting functions. We're looking for someone who enjoys building products, solving customer problems and moving quickly.
Location: Hybrid working – 1 day per week in London. Travel to Europe approximately 3–4 times per year.
Why apply?
- Own the architecture of a business-critical data platform.
- Influence technology strategy from day one.
- Lead and develop the data function.
- Work in a collaborative, engineering-first environment.
- Build products that have a direct impact on customers.
- Join a growing fintech where your decisions will genuinely shape the future of the platform.
If you're passionate about modern data architecture, enjoy building scalable data products, and want to make a real impact within a growing fintech, we'd love to hear from you.
Data Architect in London employer: develop
Join a dynamic consultancy that prioritises employee growth and fosters a collaborative work culture in the heart of London. With a focus on health sector transformation, we offer competitive salaries, hybrid working options, and opportunities to lead impactful projects while mentoring the next generation of consultants. Our commitment to professional development ensures that you will thrive in an environment that values innovation and strategic thinking.
StudySmarter Expert Advice🤫
We think this is how you could land Data Architect in London
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We think you need these skills to ace Data Architect 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 develop, 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 develop. 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 develop
✨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 develop!
✨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.
