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- Tasks: Own and maintain data pipelines while collaborating with analysts and data scientists.
- Company: Join black.ai, a passionate team making a real impact on healthcare.
- Benefits: Competitive salary, flexible working hours, and opportunities for professional growth.
- Other info: Be part of a dynamic team focused on innovation and collaboration.
- Why this job: Make a difference in healthcare by optimising data for real-time insights.
- Qualifications: 4+ years in data engineering, strong SQL skills, and cloud platform familiarity.
The predicted salary is between 50000 - 70000 £ per year.
black.ai is seeking a Mid-level Data Engineer to support the UK market. In this role, you will own and maintain data pipelines, collaborate with analysts and data scientists to deliver clean data, and design new pipelines for optimization.
Ideal candidates have at least 4 years of experience in data engineering, strong SQL skills, and familiarity with cloud platforms. You'll be part of a passionate team making a real impact on healthcare.
Data Engineer - Personalisation & Real-Time Pipelines (UK) employer: black.ai
Contact Detail:
black.ai Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineer - Personalisation & Real-Time Pipelines (UK)
✨Tip Number 1
Network like a pro! Reach out to current employees at black.ai on LinkedIn or other platforms. A friendly chat can give you insider info and might just get your foot in the door.
✨Tip Number 2
Show off your skills! Prepare a portfolio showcasing your data pipelines and projects. When you get that interview, having tangible examples will set you apart from the crowd.
✨Tip Number 3
Stay updated with the latest trends in data engineering. Follow relevant blogs, podcasts, or webinars. This not only boosts your knowledge but also shows your passion for the field during interviews.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing candidates who take the initiative to connect directly with us.
We think you need these skills to ace Data Engineer - Personalisation & Real-Time Pipelines (UK)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in data engineering, especially with SQL and cloud platforms. We want to see how your skills align with the role, so don’t be shy about showcasing relevant projects!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re passionate about data engineering and how you can contribute to our team at black.ai. Keep it concise but impactful!
Showcase Your Problem-Solving Skills: In your application, mention specific challenges you've tackled in previous roles. We love seeing how you’ve optimised data pipelines or collaborated with analysts to deliver clean data. Real examples make a difference!
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 the role. Plus, it’s super easy – just a few clicks!
How to prepare for a job interview at black.ai
✨Know Your Data Pipelines
Make sure you can talk confidently about your experience with data pipelines. Be ready to discuss specific projects where you've owned and maintained these pipelines, as well as any challenges you faced and how you overcame them.
✨Brush Up on SQL Skills
Since strong SQL skills are a must for this role, review key concepts and be prepared to answer technical questions or even solve problems on the spot. Practising common SQL queries will help you feel more confident during the interview.
✨Familiarise Yourself with Cloud Platforms
If you have experience with cloud platforms, make sure to highlight it. If not, do some research on popular ones like AWS or Google Cloud. Understanding how they integrate with data engineering will show your commitment to the role.
✨Show Your Passion for Healthcare
Since you'll be part of a team making an impact on healthcare, express your enthusiasm for the industry. Share any relevant experiences or insights that demonstrate your interest in using data to improve healthcare outcomes.