At a Glance
- Tasks: Design and implement cloud-native data platforms while advising clients on AI solutions.
- Company: Join Credera, a tech company focused on innovation and client impact.
- Benefits: Competitive salary, comprehensive benefits, and a flexible hybrid working model.
- Other info: Collaborative culture with excellent career growth opportunities.
- Why this job: Shape the future of data and AI while working on exciting projects with diverse clients.
- Qualifications: 5+ years in data & analytics, strong cloud architecture skills, and experience leading teams.
The predicted salary is between 65000 - 80000 ÂŁ per year.
Are you passionate about developing a career in technology? Does the idea of working for different clients on complex business-critical IT projects excite you? If yes, then read on! This role combines strong foundations in cloud‑native data platform architecture with practical experience of modern AI‑enabled data solutions, while remaining focused on hands‑on delivery and client value.
We are looking for an experienced Data & AI Platform Architect with expertise in cloud‑native data, analytics and AI platforms across the data value chain. You will help design scalable, secure and sustainable platforms for our clients, integrating batch and real‑time processing, robust data management practices, and modern analytics and AI capabilities.
You should bring practical experience of data & analytics platforms, alongside an understanding of how Machine Learning, Generative AI and Large Language Models can be applied within enterprise solutions. This role is suited to someone who is comfortable shaping architecture, advising clients, and leading small teams or workstreams, while remaining close to delivery.
Responsibilities- Define and implement platform architectures for cloud-native PaaS and SaaS applications with a focus on data, analytics and AI.
- Design scalable data and AI platform components that support client business and strategic goals.
- Ensure seamless data flow across microservices‑and API‑driven architectures.
- Establish best practices for real‑time and batch processing in hybrid cloud environments.
- Define and promote principles and best practices to help clients leverage data using modern analytics technologies.
- Support the integration of Machine Learning and Generative AI capabilities into data platforms or solutions, ensuring they are scalable, secure and aligned to business needs.
- Contribute to AI and LLM proof of concepts and early industrialisation activities, also demonstrating how modern generative models or agentic development approaches can enhance data processing and analytics solutions.
- Contribute to the adoption of advanced analytics and AI capabilities, including MLOps and AIOps.
- Ensure data security and compliance with relevant standards and regulations, particularly in public sector and regulated environments.
- Implement robust data management and governance strategies to support long‑term sustainability.
- Apply strong understanding of the full data lifecycle to architecture and delivery decisions.
- Advise clients on data platform and analytics modernisation strategies.
- Work closely with business, engineering and policy teams to align solutions with organisational goals.
- Translate business needs into scalable technical solutions and provide clear architectural guidance.
- Support and mentor engineers and other team members within small delivery teams, helping to foster innovation and quality in delivery.
- Proven experience (5+ years) in data & analytics, and AI solution design and delivery.
- Experience leading solution implementation for small teams or workstreams.
- Strong understanding of cloud-centric approaches to solution design and architecture.
- Strong understanding of core data management concepts across the full data lifecycle.
- Good understanding of CI/CD and modern approaches to IT and infrastructure delivery.
- Able to clearly articulate key concepts in AI, Machine Learning and Data Mining, and explain how they can be leveraged effectively within modern data platform solutions.
- Public sector or regulated industry experience is desirable, including sectors such as government or healthcare.
- Expertise in cloud data platforms across AWS or Azure.
- Experience with modern data warehouse and lakehouse ecosystems such as BigQuery, Redshift, Synapse, Snowflake or Databricks.
- Familiarity with Machine Learning and Generative AI technologies. Active interest in agentic development approaches.
- Familiarity with SQL and Python or Java.
- Familiarity with Infrastructure as Code for cloud platform delivery.
- Cloud platform architecture certification is desirable, with a data or AI specialism beneficial.
- Strong stakeholder management and consulting skills.
- Ability to collaborate effectively across cross‑functional teams.
- Ability to translate business objectives into pragmatic, scalable technical solutions.
- Experience contributing to or supporting solutions through enterprise architectural governance.
- Strong communication skills with the confidence to advise clients and delivery teams alike.
Along with a great company culture, Credera provides an exceptional compensation package including a competitive salary (£65,000‑80,000) and a comprehensive benefits plan.
Hybrid Working ModelAt Credera we operate a flexible hybrid working model. This includes 3 days per week working onsite – either at client site (as required) or in your local Credera office (London, Manchester, Leeds or Newcastle). We value collaboration and client impact, so our hybrid model is designed to strike a balance between flexibility, in‑person connection, and delivering exceptional outcomes for our clients.
Data Platform Architect, Managing Consultant in London employer: Credera
Contact Detail:
Credera Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Platform Architect, Managing Consultant in London
✨Tip Number 1
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 the role you want. You never know who might have the inside scoop on job openings!
✨Tip Number 2
Show off your skills! Create a portfolio or a personal project that highlights your expertise in data platforms and AI solutions. This is a great way to demonstrate your hands-on experience and make you stand out during interviews.
✨Tip Number 3
Prepare for those interviews! Research common questions related to data architecture and AI technologies. Practice articulating how your experience aligns with the job description, especially around cloud-native solutions and real-time processing.
✨Tip Number 4
Don’t forget to apply through our website! We love seeing candidates who are genuinely interested in joining us at StudySmarter. Tailor your application to highlight your relevant experience and show us why you’re the perfect fit for the role.
We think you need these skills to ace Data Platform Architect, Managing Consultant in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that align with the Data Platform Architect role. Highlight your cloud-native data platform architecture experience and any relevant AI projects you've worked on.
Craft a Compelling Cover Letter: Use your cover letter to tell us why you're passionate about technology and how your background makes you a great fit for this role. Share specific examples of your work with data and analytics platforms to really stand out.
Showcase Your Technical Skills: Don’t forget to mention your expertise in cloud platforms like AWS or Azure, and any experience with modern data ecosystems. We want to see how you can contribute to our clients' needs with your technical know-how.
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 shows you’re keen on joining our team!
How to prepare for a job interview at Credera
✨Know Your Tech Inside Out
Make sure you brush up on your knowledge of cloud-native data platforms, AI technologies, and analytics. Be ready to discuss how you've applied these in past projects, especially in real-time processing and data management.
✨Showcase Your Problem-Solving Skills
Prepare to share specific examples of how you've tackled complex IT challenges. Think about times when you had to design scalable solutions or integrate machine learning capabilities, and be ready to explain your thought process.
✨Understand the Client's Needs
Research the company and its clients before the interview. Understand their business goals and how your expertise can help them achieve those. This will show that you're not just technically skilled but also client-focused.
✨Communicate Clearly and Confidently
Practice articulating your ideas clearly, especially when discussing technical concepts. Remember, you might need to explain complex topics like AI and data lifecycle management to non-technical stakeholders, so clarity is key!