At a Glance
- Tasks: Design and optimise data pipelines using GCP and collaborate with cross-functional teams.
- Company: Join Ki, a pioneering global algorithmic insurance carrier transforming the industry.
- Benefits: Gain hands-on experience in a fast-growing tech environment with a focus on innovation.
- Other info: Inclusive culture that values diverse perspectives and fosters career growth.
- Why this job: Be part of a mission to revolutionise insurance with cutting-edge technology and data solutions.
- Qualifications: Experience in data modelling, Big Query, Python, SQL, and cloud infrastructure.
The predicted salary is between 63000 - 77000 £ per year.
Ki’s mission is simple: Digitally transform and revolutionise a 335‑year‑old market. Working with Google and UCL, Ki has created a platform that uses algorithms, machine learning and large language models to give insurance brokers quotes in seconds, rather than days.
Ki is proudly the biggest global algorithmic insurance carrier and the fastest growing syndicate in the Lloyd’s of London market, being the first ever to make $100m in profit in 3 years. Ki’s teams have varied backgrounds and work together in an agile, cross‑functional way to build the very best experience for its customers. Ki has big ambitions but needs more excellent minds to challenge the status‑quo and help it reach new horizons.
While our broker platform is the core technology crucial to Ki's success, this role will focus on supporting the middle/back‑office operations that will lay the foundations for further and sustained success. We're a multi‑disciplined team, bringing together expertise in software and data engineering, full stack development, platform operations, algorithm research, and data science. Our squads focus on delivering high‑impact solutions, favouring a highly iterative, analytical approach.
What you will be doing:
- Work with both the business teams (finance and actuary initially), data scientists and engineers to design, build, optimise and maintain production‑grade data pipelines and reporting from an internal Data warehouse solution, based on GCP/Big Query.
- Work with finance, actuaries, data scientists and engineers to understand how we can make best use of new internal and external data sources.
- Work with our delivery partners at EY/IBM to ensure robustness of design and engineering of the data model/MI and reporting which can support our ambitions for growth and scale.
- BAU ownership of data models, reporting and integrations/pipelines.
- Create frameworks, infrastructure and systems to manage and govern Ki’s data asset.
- Produce detailed documentation to allow ongoing BAU support and maintenance of data structures, schema, reporting etc.
- Work with the broader Engineering community to develop our data and MLOps capability infrastructure.
- Ensure data quality, governance, and compliance with internal and external standards.
- Monitor and troubleshoot data pipeline issues, ensuring reliability and accuracy.
What you will bring to the role:
- Experience designing data models and developing industrialised data pipelines.
- Strong knowledge of database and data lake systems.
- Hands‑on experience in Big Query, dbt, GCP cloud storage.
- Proficient in Python, SQL and Terraform.
- Knowledge of Cloud SQL, Airbyte, Dagster.
- Comfortable with shell scripting with Bash or similar.
- Experience provisioning new infrastructure in a leading cloud provider, preferably GCP.
- Proficient with Tableau Cloud for data visualization and reporting.
- Experience creating DataOps pipelines.
- Comfortable working in an Agile environment, actively participating in approaches such as Scrum or Kanban.
Ki Values:
- Know Your Customer: Put yourself in their shoes. Understand and balance the different needs of our customers, acting with integrity and empathy to create something excellent.
- Grow Together: Empower each other to succeed. Recognise the work of our teams, while celebrating individual success. Embrace diverse perspectives so we can develop and grow together.
- Be Courageous: Think big, push boundaries. Don’t be afraid to fail because that’s how we learn. Test, adapt, improve – always strive to be better.
Our culture: At Ki, we are committed to creating an inclusive environment where every colleague is valued and respected for who they are and can do the best work of their careers. Inclusion is a critical foundation of our business and people strategies and supports our vision of becoming a market‑leading, digital and data‑led specialty insurance business. An inclusive workplace fuels innovation because creativity thrives when everyone feels valued, respected, and supported to drive it. So, no matter who you are, where you’re from, how you think, or who you love, we believe you should be you.
Seniority level: Mid‑Senior level
Employment type: Temporary
Job function: Insurance
Temporary GCP Data Engineer 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 Temporary GCP Data Engineer 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 Temporary GCP Data Engineer 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.
