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- Tasks: Design and optimise scalable data platforms for AI-driven analytics.
- Company: Dynamic organisation transforming its data strategy with innovative cloud-native architecture.
- Benefits: Flexible hybrid work, competitive salary, and opportunities for professional growth.
- Why this job: Shape the future of data ecosystems and drive impactful AI initiatives.
- Qualifications: Strong data architecture experience and proficiency in SQL and cloud tools.
- Other info: Collaborative environment with a focus on modern data science workflows.
The predicted salary is between 36000 - 60000 ÂŁ per year.
This organisation is undergoing a continued large-scale transformation, placing modern data strategy at the heart of its evolution. With a growing portfolio of advanced data products and AI initiatives, they are investing in scalable cloud-native architecture that enables powerful analytics and intelligent services across the entire business.
This is an opportunity to play a central role in shaping their long‑term data ecosystem, with hands‑on ownership of model design, platform optimisation, and data governance standards within an extremely established data science, analytics engineering, AI engineering, and data platform engineering team.
What You’ll Be Doing- Design scalable data platforms using modern architecture principles across development, staging, and production environments.
- Lead the modelling of business‑critical domains into dimensional structures that support BI, regulatory reporting, and ML pipelines.
- Integrate data from diverse internal and external sources, including cloud services, APIs, and third‑party systems.
- Define and maintain semantic layers using tools such as DBT and Delta Live Tables, ensuring consistency across dashboards and analytics tools.
- Enable data products that support AI and GenAI use cases, including vector‑ready and model‑optimised datasets.
- Develop and maintain secure data access controls, including RBAC, token policies, and anonymisation mechanisms.
- Support batch and real‑time data flows using tools like Airflow, Kafka, Spark, and Terraform.
- Monitor cloud platform performance and implement cost‑control measures while improving reliability.
- Collaborate with product, engineering, and governance teams to define standards, lead architectural discussions, and contribute to strategic decisions.
- Write and review architectural documentation and technical design guidance.
- Strong experience in data architecture, including designing data models from scratch and implementing schemas like star, snowflake, and canonical enterprise structures.
- A track record of working across domains such as pricing, claims, fraud, policy, and quote data.
- High proficiency in SQL and cloud‑native tools such as Databricks, Snowflake, and AWS environments.
- Hands‑on experience delivering semantic layers using DBT and building analytics‑friendly data structures.
- Experience working with streaming and batch pipelines and exposure to the tools that support them.
- Confidence designing infrastructure to support modern data science workflows, including GenAI, RAG pipelines, and ML inference.
- Good understanding of data privacy, retention, and access control frameworks in regulated environments.
- A collaborative mindset, with experience working across business and technical teams to deliver scalable, reusable data components.
Data Architect in England employer: Xcede
Contact Detail:
Xcede Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Architect in England
✨Network Like a Pro
Get out there and connect with people in the industry! Attend meetups, webinars, or even just grab a coffee with someone who’s already in a data role. Building relationships can lead to insider info about job openings that aren’t even advertised yet.
✨Show Off Your Skills
Don’t just tell them what you can do; show them! Create a portfolio of your projects, especially those related to data architecture. Use platforms like GitHub to showcase your work and make it easy for recruiters to see your skills in action.
✨Ace the Interview
Prepare for your interviews by practising common data architecture questions and scenarios. Think about how you’d approach real-world problems they might throw at you. Remember, it’s not just about answering correctly but also demonstrating your thought process.
✨Apply Through Us!
If you’re keen on this Data Architect role, don’t hesitate to apply through our website! We’re here to help you land that dream job, so take advantage of our resources and support to make your application stand out.
We think you need these skills to ace Data Architect in England
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experience mentioned in the job description. Highlight your data architecture expertise and any relevant projects you've worked on. We want to see how you can fit into our team!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about data architecture and how your background aligns with our goals at StudySmarter. Keep it engaging and personal, so we get a sense of who you are.
Showcase Your Technical Skills: Since this role involves a lot of technical work, make sure to list your proficiency in SQL, cloud-native tools, and any experience with data modelling. We love seeing hands-on experience, so don’t hold back on the details!
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’re considered for the role. Plus, it’s super easy – just follow the prompts!
How to prepare for a job interview at Xcede
✨Know Your Data Architecture Inside Out
Make sure you’re well-versed in data architecture principles, especially the ones mentioned in the job description. Brush up on designing data models like star and snowflake schemas, and be ready to discuss your hands-on experience with tools like Databricks and Snowflake.
✨Showcase Your Problem-Solving Skills
Prepare to share specific examples of how you've tackled challenges in data integration or platform optimisation. Think about times when you’ve had to lead architectural discussions or collaborate with cross-functional teams, as this will demonstrate your collaborative mindset.
✨Familiarise Yourself with Their Tech Stack
Get to grips with the tools and technologies mentioned in the job description, such as Airflow, Kafka, and Terraform. Being able to speak confidently about these tools and how you’ve used them in past projects will set you apart from other candidates.
✨Prepare Questions That Matter
Think of insightful questions to ask during the interview that show your interest in their data strategy and AI initiatives. This could include inquiries about their current data governance standards or how they envision the evolution of their data ecosystem.