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- Tasks: Build and maintain scalable data pipelines while ensuring top-notch data quality.
- Company: Leading tech company in Greater London with a focus on innovation.
- Benefits: Private medical insurance, stock options, and a supportive work environment.
- Why this job: Join us to shape the future of the (re)insurance market with your skills.
- Qualifications: Fluency in Python and SQL, plus experience with production-level data pipelines.
- Other info: Dynamic team environment with opportunities for growth and innovation.
The predicted salary is between 36000 - 60000 £ per year.
A leading tech company in Greater London is looking for a Data Engineer to build and maintain scalable data pipelines and ensure data quality. Ideal candidates should be fluent in Python and SQL, with practical experience in production-level data pipelines utilizing tools like Airflow or Dagster.
The role offers generous benefits including private medical insurance, stock options, and a supportive work environment focused on innovation. Join us to shape the future of the (re)insurance market.
Data Engineer — Scalable Pipelines & Platform Insights employer: Artificial Labs
Contact Detail:
Artificial Labs Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineer — Scalable Pipelines & Platform Insights
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with current employees at the company. You never know who might give you a heads-up about an opening or refer you directly!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your data pipelines and projects. Use GitHub or a personal website to demonstrate your Python and SQL prowess. This will make you stand out when we’re looking for candidates.
✨Tip Number 3
Prepare for the technical interview! Brush up on your knowledge of tools like Airflow or Dagster. Practice coding challenges and be ready to discuss your past experiences with scalable data solutions. We love seeing how you think!
✨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, it shows you’re genuinely interested in joining our innovative team!
We think you need these skills to ace Data Engineer — Scalable Pipelines & Platform Insights
Some tips for your application 🫡
Show Off Your Skills: Make sure to highlight your Python and SQL skills in your application. We want to see how you've used these languages in real-world projects, especially when it comes to building data pipelines.
Talk About Your Experience: If you've worked with tools like Airflow or Dagster, let us know! Share specific examples of how you've implemented these tools in your previous roles to manage data workflows.
Keep It Relevant: Tailor your application to the job description. We’re looking for someone who can maintain scalable data pipelines, so make sure your experience aligns with that focus.
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 don’t miss out on any important updates from us!
How to prepare for a job interview at Artificial Labs
✨Know Your Tech Stack
Make sure you’re well-versed in Python and SQL, as these are crucial for the role. Brush up on your knowledge of data pipelines and tools like Airflow or Dagster, and be ready to discuss your hands-on experience with them.
✨Showcase Your Problem-Solving Skills
Prepare to share specific examples of challenges you've faced in previous projects. Highlight how you approached these problems, the solutions you implemented, and the impact they had on data quality and pipeline efficiency.
✨Understand the Company’s Vision
Research the company’s focus on innovation within the (re)insurance market. Be prepared to discuss how your skills and experiences align with their goals and how you can contribute to shaping the future of their data infrastructure.
✨Ask Insightful Questions
Prepare thoughtful questions about the team dynamics, the technologies they use, and their approach to data quality. This shows your genuine interest in the role and helps you assess if it’s the right fit for you.
