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- Tasks: Design and develop data processing pipelines and reporting solutions using Big Query and Tableau.
- Company: Dynamic insurance tech firm in the UK with an innovative team.
- Benefits: Hybrid work model, agile methodologies, and opportunities for collaboration.
- Why this job: Join a cutting-edge team and optimise data utilisation in a fast-paced environment.
- Qualifications: Strong skills in Python, SQL, and experience with cloud technologies.
The predicted salary is between 36000 - 60000 £ per year.
A dynamic insurance technology firm in the UK is seeking a Data Engineer to join their innovative team. You will design and develop complex data processing pipelines and reporting solutions utilizing Big Query and Tableau. Collaboration with finance and data science teams is essential to optimize data utilization. The ideal candidate should have a strong command of Python, SQL, and experience in cloud technologies. A hybrid work model with a focus on agile methodologies is supported.
GCP Data Engineer: Pipelines, BI & MLOps employer: Ki
Contact Detail:
Ki Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land GCP Data Engineer: Pipelines, BI & MLOps
✨Tip Number 1
Network like a pro! Reach out to folks in the insurance tech space, especially those working with data pipelines and BI. A friendly chat can open doors that a CV just can't.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects with Python, SQL, and cloud technologies. This is your chance to demonstrate what you can do beyond the written application.
✨Tip Number 3
Prepare for the interview by brushing up on agile methodologies and how they apply to data engineering. We want to see you shine when discussing collaboration with finance and data science teams!
✨Tip Number 4
Don't forget to apply through our website! It’s the best way to ensure your application gets the attention it deserves. Plus, we love seeing candidates who take that extra step.
We think you need these skills to ace GCP Data Engineer: Pipelines, BI & MLOps
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with Python, SQL, and cloud technologies. We want to see how your skills align with the role of a Data Engineer, 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 excited about the role and how you can contribute to our innovative team. Let us know how your past experiences have prepared you for this position.
Showcase Collaboration Skills: Since collaboration with finance and data science teams is key, mention any past experiences where you worked in cross-functional teams. We love to see how you can bring people together to optimise data utilisation!
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 and you’re done!
How to prepare for a job interview at Ki
✨Know Your Tech Stack
Make sure you brush up on your Python, SQL, and cloud technologies before the interview. Be ready to discuss how you've used these tools in past projects, especially in building data pipelines or BI solutions.
✨Showcase Your Collaboration Skills
Since this role involves working closely with finance and data science teams, prepare examples of how you've successfully collaborated in the past. Highlight any agile methodologies you've used to enhance teamwork and project outcomes.
✨Prepare for Technical Questions
Expect some technical questions related to Big Query and Tableau. Practise explaining your thought process when designing data processing pipelines, as well as any challenges you've faced and how you overcame them.
✨Ask Insightful Questions
At the end of the interview, don’t forget to ask questions! Inquire about the company's approach to data utilisation and how they envision the role evolving. This shows your genuine interest and helps you gauge if it's the right fit for you.