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- Tasks: Lead a team to build and maintain AI-driven revenue optimisation solutions.
- Company: Join a dynamic start-up revolutionising hotel pricing with cutting-edge technology.
- Benefits: Enjoy remote work flexibility and competitive salary up to £110k.
- Why this job: Be part of an innovative team making a real impact in a £7 billion industry.
- Qualifications: Experience in data engineering and MLOps is essential.
- Other info: Meet the team quarterly in London for collaboration and strategy sessions.
The predicted salary is between 66000 - 88000 £ per year.
Are you a data savvy hands-on technology leader? You could be joining a well-funded and growing hotel revenue optimisation technology start-up that uses AI and complex algorithms to enable hotels to price their rooms according to demand; this is a £7 billion a year industry and the product is in great demand.
As a Data Engineering Lead you will lead a small, experienced Science Platform team that are building and maintaining the Platform as a Service (PaaS) that enables development and operation of AI-first revenue optimisation solutions. You'll remain hands-on 80-90% of the time, driving architectural decisions and ensuring the platform's scalability, reliability and performance. Contributing to longer term strategy, you will partner with the Product Manager to define and execute technical strategy and the product roadmap and take ownership for the success of critical platform components including data science workflows, cloud environments, observability systems and CI/CD infrastructure.
Location / WFH: You can work from home most of the time but must be commutable to London (within 3-4 hours) as you'll be expected to meet up with the team there around once a quarter.
About you:
Data Engineering Lead MLOps AI PaaS employer: Click To Hired
Contact Detail:
Click To Hired Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineering Lead MLOps AI PaaS
✨Tip Number 1
Familiarise yourself with the latest trends in MLOps and AI technologies. Being well-versed in these areas will not only help you during interviews but also demonstrate your passion and commitment to the field.
✨Tip Number 2
Network with professionals in the data engineering and MLOps space. Attend relevant meetups or webinars, and connect with people on LinkedIn. This can lead to valuable insights and potentially even referrals for the position.
✨Tip Number 3
Prepare to discuss your hands-on experience with cloud environments and CI/CD infrastructure. Be ready to share specific examples of how you've driven architectural decisions and improved platform performance in previous roles.
✨Tip Number 4
Research the company’s product and its impact on the hotel industry. Understanding their technology and how it fits into the market will allow you to speak knowledgeably about their goals and how you can contribute to their success.
We think you need these skills to ace Data Engineering Lead MLOps AI PaaS
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in data engineering, MLOps, and AI technologies. Emphasise your leadership skills and hands-on experience with platforms similar to PaaS.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for data engineering and your understanding of the hotel revenue optimisation industry. Mention specific projects or achievements that demonstrate your ability to lead a team and drive architectural decisions.
Showcase Technical Skills: In your application, clearly outline your technical skills related to cloud environments, CI/CD infrastructure, and observability systems. Use specific examples to illustrate how you've successfully implemented these in past roles.
Highlight Collaboration Experience: Since the role involves partnering with a Product Manager, include examples of successful collaborations in your previous positions. This will show your ability to work cross-functionally and contribute to product strategy.
How to prepare for a job interview at Click To Hired
✨Show Your Technical Expertise
As a Data Engineering Lead, you'll need to demonstrate your hands-on experience with MLOps and AI technologies. Be prepared to discuss specific projects where you've implemented data pipelines or optimised algorithms, showcasing your technical skills and problem-solving abilities.
✨Understand the Business Context
Familiarise yourself with the hotel revenue optimisation industry and how AI impacts pricing strategies. Showing that you understand the business model and can align technical decisions with business goals will impress the interviewers.
✨Highlight Leadership Experience
Since this role involves leading a team, be ready to share examples of how you've successfully managed teams in the past. Discuss your leadership style, how you motivate team members, and any challenges you've overcome in a leadership capacity.
✨Prepare for Scenario-Based Questions
Expect scenario-based questions that assess your decision-making and architectural design skills. Think about how you would approach scalability, reliability, and performance issues in a cloud environment, and be ready to articulate your thought process clearly.
