At a Glance
- Tasks: Design and build high-fidelity data pipelines using semantic models.
- Company: Fast-growing AI-native consultancy based in London.
- Benefits: Hybrid working model, high autonomy, and significant responsibility.
- Other info: Opportunity to work with cutting-edge technology in a dynamic environment.
- Why this job: Shape the future of AI-native products and standards.
- Qualifications: 5–8 years of data engineering experience with strong SQL and Python skills.
The predicted salary is between 43200 - 72000 £ per year.
A fast-growing AI-native consultancy in London is seeking an experienced Data Engineer to design and build high-fidelity data pipelines aligned with semantic models. The ideal candidate will have 5–8 years of experience in data engineering, strong SQL and Python skills, and familiarity with cloud platforms like AWS, Azure, or GCP. This role offers a hybrid working model, high autonomy, and significant responsibility in shaping AI-native products and standards.
Senior Data Engineer - Semantic & Knowledge-Graph Pipelines employer: develop
Join a fast-growing AI-native consultancy in London, where innovation meets opportunity. We offer a dynamic work culture that fosters creativity and collaboration, alongside a hybrid working model that promotes work-life balance. With a strong focus on employee growth, you will have the chance to shape cutting-edge AI products while enjoying the autonomy and responsibility that comes with this pivotal role.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Engineer - Semantic & Knowledge-Graph Pipelines
✨Tip Number 1
Network like a pro! Reach out to your connections in the data engineering field, especially those who work with semantic models or AI. A friendly chat can lead to insider info about job openings that aren't even advertised yet.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your best data pipelines and projects. This is your chance to demonstrate your SQL and Python prowess, so make it visually appealing and easy to navigate.
✨Tip Number 3
Prepare for the interview like it's a big data project! Research the company’s current projects and think about how your experience aligns with their needs. Be ready to discuss your past work with cloud platforms like AWS, Azure, or GCP.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities waiting for talented folks like you. Plus, applying directly shows your enthusiasm and commitment to joining our team.
We think you need these skills to ace Senior Data Engineer - Semantic & Knowledge-Graph Pipelines
Some tips for your application 🫡
Show Off Your Skills:Make sure to highlight your SQL and Python expertise in your application. We want to see how your experience aligns with the role, so don’t hold back on showcasing your best projects!
Tailor Your Application:Take a moment to customise your CV and cover letter for this specific role. Mention your experience with cloud platforms like AWS, Azure, or GCP, as it’s super relevant to what we’re looking for.
Be Clear and Concise:When writing your application, keep it straightforward and to the point. We appreciate clarity, so make sure your key achievements and experiences shine through without unnecessary fluff.
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 this exciting opportunity!
How to prepare for a job interview at develop
✨Know Your Data Inside Out
Make sure you brush up on your SQL and Python skills before the interview. Be ready to discuss specific projects where you've designed and built data pipelines, especially those that align with semantic models. This will show your depth of knowledge and experience.
✨Familiarise Yourself with Cloud Platforms
Since the role requires familiarity with AWS, Azure, or GCP, take some time to review the key features and services of these platforms. Be prepared to discuss how you've used them in past projects, as this will demonstrate your practical experience and adaptability.
✨Showcase Your Problem-Solving Skills
Data engineering often involves tackling complex problems. Think of examples where you've faced challenges in your previous roles and how you overcame them. This will highlight your critical thinking and problem-solving abilities, which are crucial for this position.
✨Emphasise Autonomy and Responsibility
This role offers high autonomy, so be ready to discuss how you've taken initiative in past projects. Share examples where you've shaped products or standards, as this will illustrate your ability to work independently and make impactful decisions.
