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- Tasks: Design and implement innovative data solutions for AI-driven transformations.
- Company: WeBuild-AI transforms enterprises into AI-powered businesses with cutting-edge data architectures.
- Benefits: Gain expertise in cloud platforms, certification opportunities, and work directly with enterprise leadership.
- Why this job: Shape the future of AI integration while working in a fast-paced, innovative environment.
- Qualifications: Strong experience with AWS/Azure data services, Python proficiency, and a collaborative mindset required.
- Other info: Join us in pioneering new approaches to data and AI integration.
The predicted salary is between 48000 - 84000 £ per year.
About WeBuild-AI: WeBuild-AI are AI natives delivering 10x value for enterprise organisations. We combine highly skilled experts with our AI Launchpad, industry-aligned language models, and agents to transform enterprise organisations into AI-powered and data-driven businesses. We work with enterprise organisations on a global stage, reinventing how they design, build, and operate AI powered software at scale with speed.
Our Purpose: At WeBuild-AI, we’re not just building data architectures—we’re building the foundation for AI-powered business transformation that creates lasting impact. Our teams are pioneering new approaches that fundamentally change how enterprises leverage their data assets, unlocking possibilities that were previously unimaginable. We believe that a modular and composable data architecture is the cornerstone of true AI transformation, and we’re looking for visionaries who share our passion for pushing boundaries.
Role Overview: As a Platform Engineer at WeBuild-AI, you will design and implement cutting-edge data solutions that form the foundation of our customers' AI-driven transformations. You’ll work with our Pathway platform to enable rapid strategy definition, technology capability validation, and new venture launches for our global enterprise clients. This role offers the unique opportunity to shape how entire industries approach data and AI integration.
Key Responsibilities:
- Work with clients to understand their data landscape and transformation needs.
- Establish data strategy roadmaps and build scalable data platforms.
- Design and implement scalable data architectures to support AI-driven solutions.
- Develop data solutions across a raft of AWS and Azure data services.
- Design and implement data mesh and data fabric solutions to optimise data discover, accessibility and governance.
- Establish the required governance and control planes for structured and unstructured data interaction for AI systems.
- Collaborate with AI Engineers to ensure data structures support advanced AI capabilities.
- Support the ongoing development of our Pathway platform and play a key role in the creation and ongoing delivery of AI agents across the end to end data lifecycle.
- Challenge conventional approaches to discover breakthrough data solutions that unlock AI innovation for customers.
Required Skills & Experience:
- You need to be equally adept at designing data driven platforms, as well as getting your fingers on key boards to build them.
- Strong experience with AWS data services with exposure to AI systems and/or Azure data services.
- Proficiency with Python for data processing and pipeline development.
- Experience in building scalable and resilient data platforms in the public cloud.
- Data modelling and wrangling expertise to support advanced analytical use cases and ML, AI opportunities.
- Experience with containerisation technologies (Docker, Kubernetes) for scalable data solutions.
- Experience with vector databases and graph databases.
- Understanding of data mesh-fabric approaches and modern data architecture patterns.
- Familiarity with AI/ML workflows and their data requirements.
- Experience with API specifications and data integrations across ETL and streaming services.
- Familiarity with AI developer tools and desire to use them to 10x your throughput.
- Collaborative approach and excellent communication skills.
- Strong problem-solving abilities and creative thinking, with critical thinking credentials to solve complex business challenges across a range of industries.
The Mindset We Value:
- Frontier Thinking: We’re looking for individuals who consistently ask "what if?" and aren’t satisfied with the status quo.
- Adaptable Learning: The AI landscape evolves weekly. We need team members who thrive in this rapid change.
- Client Empathy: You must be able to translate complex technical concepts into value that resonates with business stakeholders.
- Speed with Purpose: We move fast, but always with clear intent.
Growth Opportunities:
- Expand your expertise across multiple cloud platforms and emerging data technologies.
- Gain certification in cutting-edge AI, data and knowledge graph technologies.
- Work directly with enterprise leadership to shape AI strategy.
- Develop deep specialisation in industry-specific solutions.
- Contribute to our thought leadership and IP development.
- Shape the future direction of our Pathway platform.
We appreciate every application we receive. Due to high interest, if you don’t hear back from us within 2 weeks, unfortunately it means we won’t be moving forward with your application this time — but we truly thank you for considering us and wish you all the best in your search.
Data Platform Engineer employer: WeBuild-AI
Contact Detail:
WeBuild-AI Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Platform Engineer
✨Tip Number 1
Familiarise yourself with the specific AWS and Azure data services mentioned in the job description, such as AWS DataZone and Azure OpenAI. Having hands-on experience or projects that showcase your skills with these technologies can set you apart during discussions.
✨Tip Number 2
Demonstrate your understanding of data mesh and data fabric concepts. Prepare to discuss how you've applied these approaches in previous roles or projects, as this will show your alignment with WeBuild-AI's vision for modular data architectures.
✨Tip Number 3
Highlight your collaborative skills and ability to communicate complex technical ideas to non-technical stakeholders. Be ready to share examples of how you've successfully worked with clients or teams to drive AI transformation initiatives.
✨Tip Number 4
Stay updated on the latest trends in AI and data technologies. Being able to discuss recent advancements or emerging tools during your conversation can demonstrate your passion for the field and your commitment to continuous learning.
We think you need these skills to ace Data Platform Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience with AWS and Azure data services, Python proficiency, and any work you've done with data architectures. Use keywords from the job description to ensure your application stands out.
Craft a Compelling Cover Letter: In your cover letter, express your passion for AI and data transformation. Mention specific projects or experiences that demonstrate your ability to design and implement scalable data solutions, and how you align with WeBuild-AI's mission.
Showcase Problem-Solving Skills: Provide examples in your application of how you've tackled complex data challenges in previous roles. Highlight your creative thinking and adaptability in fast-paced environments, as these are key traits WeBuild-AI values.
Highlight Collaborative Experience: Emphasise your ability to work collaboratively with clients and teams. Mention any experience you have in translating technical concepts for non-technical stakeholders, as this will resonate well with WeBuild-AI's client empathy mindset.
How to prepare for a job interview at WeBuild-AI
✨Understand the Company and Its Vision
Before your interview, take some time to research WeBuild-AI and its mission. Familiarise yourself with their AI Launchpad and how they transform enterprise organisations. This will help you align your answers with their goals and demonstrate your genuine interest in the company.
✨Showcase Your Technical Skills
Be prepared to discuss your experience with AWS and Azure data services, as well as your proficiency in Python. Bring examples of past projects where you've designed scalable data platforms or implemented data architectures. This will highlight your technical expertise and problem-solving abilities.
✨Emphasise Collaboration and Communication
Since the role involves working closely with clients and AI engineers, be ready to share examples of how you've successfully collaborated in the past. Highlight your ability to translate complex technical concepts into business value, which is crucial for client empathy.
✨Demonstrate Frontier Thinking
WeBuild-AI values individuals who challenge the status quo. Prepare to discuss how you've approached problems with a 'what if?' mindset and any innovative solutions you've developed. This will show that you're adaptable and eager to experiment with emerging technologies.
