At a Glance
- Tasks: Build and optimise robust data pipelines using Big Query and Python.
- Company: Leading global insurance innovator in the UK with a focus on innovation.
- Benefits: Gain valuable experience in a dynamic environment with potential for growth.
- Other info: Temporary position with opportunities to collaborate with finance and engineering teams.
- Why this job: Join a rapidly growing company and make a real impact on data operations.
- Qualifications: Expertise in Big Query, Python, and Agile methodologies required.
The predicted salary is between 63000 - 77000 £ per year.
A leading global insurance innovator in the UK is seeking a Mid-Senior level professional to support their data pipeline operations.
In this role, you will work with finance, actuaries, and engineers to optimize data handling and reporting while ensuring compliance and data quality.
The ideal candidate must have expertise in Big Query and Python, as well as experience in Agile environments.
This temporary position offers a unique opportunity to contribute to a rapidly growing company focused on innovation and excellence.
#J-18808-Ljbffr
GCP Data Engineer (Temp): Build Robust Data Pipelines in England employer: Ki
At KI, we pride ourselves on being an excellent employer by fostering a collaborative and innovative work culture that empowers our employees to excel in their roles. Located in a dynamic industry, we offer competitive remuneration, comprehensive benefits, and ample opportunities for professional growth, ensuring that our team members can thrive while contributing to the future of insurance technology.
StudySmarter Expert Advice🤫
We think this is how you could land GCP Data Engineer (Temp): Build Robust Data Pipelines in England
✨Tap into Online Data Science Communities
Join online communities focused on data science like Kaggle, LinkedIn groups, or Reddit threads. These are goldmines for temporary gigs, as you can network with professionals and potentially hear about opportunities at companies like Ki before they're even advertised!
✨Show Off Your Skills With Projects
Got some cool data science projects? Showcase them on platforms like GitHub or create a personal portfolio website. This visibility is crucial for landing temporary roles—let recruiters see your actual skills in action, which can set you apart from the crowd.
✨Check Out Specialist Job Boards
For temp roles, hit up job boards dedicated to tech and data science, like Stack Overflow Jobs or DataJobs. These platforms often feature openings that you won’t find on general job sites, including contracts with companies like Ki.
✨Leverage University Resources
If you're currently at uni or recently graduated, tap into your school's career services. They often have connections with companies looking for temporary data science interns or contract workers, and they might even host job fairs with employers like Ki.
We think you need these skills to ace GCP Data Engineer (Temp): Build Robust Data Pipelines in England
Some tips for your application 🫡
Highlight Your Data Projects:When applying for a temporary data science role at Ki, make sure to showcase any relevant projects you've worked on. Whether it's a personal project, an academic undertaking, or contributions to an open-source initiative, detailing these experiences can really set you apart and demonstrate your practical skills.
Emphasise Your Analytical Skills:In your CV and cover letter, focus on the specific analytical skills that are key to data science. Mention any experience with statistical tools, programming languages like Python or R, and data visualisation software. Don't forget to include any certifications that may bolster your expertise!
Show Your Flexibility:Since this is a temporary role, it's important to convey your adaptability and willingness to learn. In your cover letter to Ki, emphasise how quickly you can get up to speed with new tools or projects. Highlight any previous experiences where you've had to adjust to new environments or challenges.
Craft a Unique Data-Driven Cover Letter:Instead of the usual generic cover letter, spice it up with some data! Maybe you’ve improved a process by 20% in a past role or cleaned a dataset with over a million entries. Use these stats to your advantage to grab Ki’s attention and show the tangible impact of your work.
How to prepare for a job interview at Ki
✨Showcase Your Analytical Skills
For a data science gig, it's crucial to demonstrate your analytical abilities. Be ready to discuss previous projects and the methodologies you used. Think about how you can quantify your impact—did your analysis improve efficiency or save costs? These are the stories that will stick with interviewers at Ki.
✨Brush Up on Technical Skills
You might face technical questions on tools relevant to data science, like Python, R, or SQL. Prepare to solve a problem live—perhaps they'll ask you to write a simple query or code snippet. It’s cool to talk about them, but we need to show we can do it in practice, especially in a temporary role where quick results matter.
✨Highlight Your Adaptability
Since this is a temporary position, emphasise your ability to learn quickly and adapt to new tools or workflows. Share examples of how you've thrived in fast-paced environments before, and how you can hit the ground running at Ki.
✨Prepare a Portfolio of Your Work
Bring your portfolio to the table—showcase projects where you've leveraged data science techniques to solve problems. Whether it’s a GitHub repository or a set of case studies, having tangible examples of your work will help you stand out and show what you bring to the team at Ki.
