Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Design and build a cutting-edge data architecture for a global AI-native platform.
- Company: Innovative tech company focused on building from the ground up.
- Benefits: High autonomy, direct access to CTO, and opportunity to shape the future.
- Why this job: Make a real impact by solving complex data challenges in a greenfield environment.
- Qualifications: Expertise in Python, AWS, and distributed data systems required.
- Other info: Exciting opportunity for those seeking ownership and growth in a dynamic setting.
The predicted salary is between 72000 - 108000 £ per year.
This is a foundational architecture seat inside a company building a globally distributed, AI-native platform from the ground up. Right now, everything is being rebuilt — how data is captured, structured, governed, and used. You won’t be inheriting legacy. You’ll be defining the system others scale on.
What You’ll Actually Be Doing
- You’ll own the entire data architecture strategy:
- Designing a modern lakehouse on AWS from first principles
- Building a real-time data layer from high-frequency, distributed systems
- Creating a data model that’s ML-ready on day one
- Defining how data flows across multiple global environments
- Solving hard problems around consistency, replication, and scale
- Turning legal / enterprise constraints into clean technical architecture
This is deep work. No fluff. No dashboards-for-the-sake-of-it.
The Real Challenge
You’re not just designing pipelines. You’re building a system that:
- Handles massive volumes of unstructured + streaming data
- Integrates graph, relational, and vector models in one ecosystem
- Powers AI systems directly from live operational data
- Scales from one site → global distributed infrastructure
- Supports enterprise clients with strict data isolation + governance
Most companies talk about this. Here, you’ll actually build it.
What Makes This Role Different
- Greenfield architecture — not fixing someone else’s mess
- Direct access to CTO — decisions move fast
- High autonomy — you own the “how”
- Real technical depth — distributed systems, not surface-level data work
- AI-native by design — not bolted on later
What We’re Looking For
You’re probably already operating at this level:
- Designing distributed data systems across teams or regions
- Deep in Python + cloud (AWS)
- Comfortable with streaming / telemetry data at scale
- Strong with Postgres and modern data patterns
- Experience with graph or vector databases
You understand:
- Data governance & tenancy
- Replication & consistency trade-offs
- Secure data sharing across organisations
You don’t need to come from a specific industry. But you do need to be comfortable operating in complex, high-ambiguity environments.
Why It’s Worth a Conversation
If you’re an architect who:
- Is bored of incremental improvements
- Wants to build something properly from scratch
- Enjoys solving hard, non-obvious problems
- And wants real ownership over a system that will scale globally… this is one of those roles.
For more info, please contact OR share your updated CV to mahanthi@Lsarecruit.co.uk
Principal Data Architect employer: LSA Recruit
Contact Detail:
LSA Recruit Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Principal Data Architect
✨Tip Number 1
Network like a pro! Reach out to people in your industry on LinkedIn or at events. A friendly chat can lead to opportunities that aren’t even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio or GitHub repository showcasing your projects, especially those related to data architecture and AI/ML. This gives potential employers a taste of what you can do.
✨Tip Number 3
Prepare for interviews by practising common questions and scenarios specific to data architecture. Think about how you’d tackle real-world problems they might throw at you.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive!
We think you need these skills to ace Principal Data Architect
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that align with the Principal Data Architect role. Highlight your expertise in Python, cloud technologies, and distributed systems to catch our eye!
Craft a Compelling Cover Letter: Use your cover letter to tell us why you're excited about building a greenfield architecture. Share specific examples of how you've tackled complex data challenges in the past – we love a good story!
Showcase Your Problem-Solving Skills: In your application, don’t just list your skills; demonstrate how you’ve used them to solve real-world problems. We’re looking for someone who can handle massive volumes of unstructured data and create innovative solutions.
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 don’t miss out on any important updates from our team!
How to prepare for a job interview at LSA Recruit
✨Know Your Data Architecture Inside Out
Make sure you’re well-versed in the principles of data architecture, especially around lakehouses and distributed systems. Brush up on your knowledge of AWS and how to design scalable solutions that handle massive volumes of unstructured data.
✨Showcase Your Problem-Solving Skills
Prepare to discuss specific challenges you've faced in previous roles, particularly around data consistency and replication. Be ready to explain how you approached these problems and the innovative solutions you implemented.
✨Demonstrate Your Technical Depth
Be prepared to dive deep into technical discussions about Python, cloud technologies, and modern data patterns. Highlight your experience with streaming data and databases like Postgres, graph, or vector models during the interview.
✨Emphasise Your Autonomy and Ownership
This role requires a high level of autonomy, so share examples of when you’ve taken ownership of projects. Discuss how you’ve successfully navigated complex environments and made impactful decisions without needing constant oversight.