Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Build core data systems and pipelines for AI research and production.
- Company: Cutting-edge AI company based in Greater London.
- Benefits: Top-tier compensation, comprehensive health benefits, and a supportive work environment.
- Other info: Dynamic role with opportunities for high-velocity experimentation.
- Why this job: Join us to create trusted data systems that drive innovation in AI.
- Qualifications: Strong data engineering experience and a passion for data quality.
The predicted salary is between 43200 - 72000 £ per year.
A cutting-edge AI company in Greater London seeks a Data Engineer to build core data systems and pipelines that drive research and production. You'll design orchestration patterns and push for data quality, enabling high-velocity experimentation. The ideal candidate has strong data engineering experience and is passionate about creating the trusted data backbone for open-weight AI systems. We offer top-tier compensation, comprehensive health benefits, and a supportive work environment.
Data Platform Staff Engineer — Scalable Pipelines employer: Reflection AI
Contact Detail:
Reflection AI Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Platform Staff Engineer — Scalable Pipelines
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with potential colleagues on LinkedIn. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data engineering projects, especially those involving scalable pipelines and orchestration patterns. This will give you an edge and demonstrate your passion for building robust data systems.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. Practice common data engineering scenarios and be ready to discuss how you've tackled challenges in past projects. Confidence is key!
✨Tip Number 4
Don’t forget to apply through our website! We love seeing candidates who are genuinely interested in joining our team. Tailor your application to highlight your experience with data quality and high-velocity experimentation to catch our eye.
We think you need these skills to ace Data Platform Staff Engineer — Scalable Pipelines
Some tips for your application 🫡
Show Your Passion for Data Engineering: When writing your application, let us see your enthusiasm for data engineering shine through! Share specific examples of projects you've worked on that demonstrate your skills in building data systems and pipelines.
Tailor Your Application: Make sure to customise your CV and cover letter to highlight your experience with orchestration patterns and data quality. We want to see how your background aligns with our mission to create a trusted data backbone for AI systems.
Be Clear and Concise: Keep your application straightforward and to the point. Use clear language to describe your achievements and avoid jargon unless it’s relevant. We appreciate clarity as much as we value technical expertise!
Apply Through Our Website: Don’t forget to submit your application through our website! It’s the best way for us to receive your details and ensures you’re considered for the role. Plus, it makes the whole process smoother for everyone involved.
How to prepare for a job interview at Reflection AI
✨Know Your Data Engineering Fundamentals
Brush up on your data engineering principles, especially around building scalable pipelines and orchestration patterns. Be ready to discuss your past experiences with data quality and how you've tackled challenges in previous roles.
✨Showcase Your Passion for AI
Since the company focuses on open-weight AI systems, demonstrate your enthusiasm for AI technologies. Share any relevant projects or research you've done that highlights your commitment to creating a trusted data backbone.
✨Prepare for Technical Questions
Expect technical questions that assess your problem-solving skills and knowledge of data systems. Practice coding challenges or system design scenarios that relate to the job description, as this will show your readiness for the role.
✨Ask Insightful Questions
At the end of the interview, ask thoughtful questions about the company's data strategy and future projects. This not only shows your interest but also helps you gauge if the company aligns with your career goals.