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 60000 - 80000 £ 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 dynamic consultancy that prioritises employee growth and fosters a collaborative work culture in the heart of London. With a focus on health sector transformation, we offer competitive salaries, hybrid working options, and opportunities to lead impactful projects while mentoring the next generation of consultants. Our commitment to professional development ensures that you will thrive in an environment that values innovation and strategic thinking.
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 interviews by brushing up on common data engineering questions, especially around cloud platforms like AWS, Azure, or GCP. We recommend doing mock interviews with friends or using online platforms to get comfortable with the format.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who take the initiative to connect directly with us.
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 skills in your application. We want to see how your experience aligns with the role, so don’t hold back on showcasing your technical prowess!
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 Authentic:Let your personality shine through in your written application. We value authenticity and want to get a sense of who you are beyond just your technical skills.
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 share examples of how you've used them in past projects, as this will demonstrate your practical experience.
✨Showcase Your Problem-Solving Skills
Data engineering often involves tackling complex problems. Think of a challenging situation you've faced in your previous roles and be ready to explain how you approached it, the solutions you considered, and the outcome. This will highlight your analytical thinking and creativity.
✨Emphasise Autonomy and Responsibility
This role offers high autonomy, so be sure to convey your ability to work independently. Share examples of times when you've taken initiative or led projects, and how you managed your responsibilities. This will reassure them that you're capable of shaping AI-native products effectively.
