At a Glance
- Tasks: Join the Portfolio Data squad to revolutionise insurance data management and insights.
- Company: Ki, a pioneering global algorithmic insurance carrier with a mission to disrupt the industry.
- Benefits: Competitive salary, recognition for efforts, and a supportive work environment.
- Why this job: Make a real impact by modernising data processes and driving innovation in insurance.
- Qualifications: Experience in software engineering, data pipelines, and cloud platforms like GCP or AWS.
- Other info: Inclusive culture that values diverse perspectives and fosters creativity.
The predicted salary is between 36000 - 60000 ÂŁ per year.
About Ki
Look at the latest headlines and you will see something Ki insures. Think space shuttles, world tours, wind farms, and even footballers' legs. Ki's mission is simple: digitally disrupt 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. It is the fastest growing syndicate in the Lloyd's of London market, and 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.
Where you come in
You will be joining the Portfolio Data squad to tackle some of the most critical challenges in transforming how we manage insurance exposure and risk aggregations. The current data estate is siloed, inefficient, and difficult to scale, so the team is designing a robust solution to support seamless data ingestion, scalable storage, and optimise for downstream use cases, including developing our algorithmic underwriting capability. Alongside this, the squad is building a trusted source of truth for insurance exposure data — aligning methodologies with the Exposure Management team and delivering intuitive, high‑value views and dashboards for Portfolio Management. By joining us, you'll help modernise our data landscape, eliminate manual and unreliable processes, and empower the business with faster, smarter, and more reliable insights.
What you will be doing
- Work with actuaries, data scientists and engineers to design, build, optimise and maintain production grade data pipelines to feed the Ki algorithm.
- Work with actuaries, data scientists and engineers to understand how we can make best use of new internal and external data sources.
- Design and engineer a data model which can support our ambitions for growth and scale.
- Create frameworks, infrastructure and systems to manage and govern Ki's data asset.
- Work with the broader Engineering community to develop our data and MLOps capability infrastructure.
Requirements
- Strong experience in software engineering with proficiency in a language such as Python for API development, data engineering and automation tasks.
- A background in working with storage solutions such as PostgreSQL, MySQL, and BigQuery.
- Experience in API development using tools such as FastAPI or Flask, enabling data access and integration across systems.
- Solid knowledge of cloud platforms (GCP and/or AWS), with the ability to design and deploy data solutions at scale.
- Experience with IAC and CI/CD pipelines to ensure reliable, repeatable, and automated deployments.
- An understanding of data modelling, ETL/ELT processes, and best practices for data quality and governance.
- Collaborative mindset, with the ability to work closely with stakeholders such as Exposure Management, Portfolio Management, and Data Science.
- Curiosity, adaptability, and enthusiasm for working in an agile, squad‑based environment.
- Experience working with large, complex, and siloed data estates, with a track record of simplifying and streamlining processes.
- A foundation in system design, with the ability to architect scalable, maintainable, and resilient data systems.
Benefits
You’ll get a highly competitive remuneration and benefits package. This is kept under constant review to make sure it stays relevant. We understand the power of saying thank you and take time to acknowledge and reward extraordinary effort by teams or individuals.
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: Full‑time
Job function: Insurance
Data Engineer employer: Ki
Contact Detail:
Ki Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Engineer
✨Tip Number 1
Network like a pro! Reach out to people in the industry, especially those at Ki or similar companies. Use LinkedIn to connect and engage with them; you never know who might help you land that interview.
✨Tip Number 2
Prepare for your interviews by understanding Ki's mission and values. Show how your skills in data engineering can help them disrupt the insurance market. Tailor your examples to highlight your experience with data pipelines and cloud platforms.
✨Tip Number 3
Don’t just wait for job openings—create opportunities! If you see a project or challenge Ki is facing, propose how you could tackle it. This shows initiative and your ability to think critically about their needs.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen. Plus, it shows you’re genuinely interested in being part of the Ki team and its innovative journey.
We think you need these skills to ace Data Engineer
Some tips for your application 🫡
Tailor Your Application: Make sure to customise your CV and cover letter for the Data Engineer role. Highlight your experience with Python, data pipelines, and cloud platforms like GCP or AWS. We want to see how your skills align with our mission to revolutionise the insurance market!
Showcase Your Projects: Include specific examples of projects you've worked on that demonstrate your ability to design and optimise data solutions. Whether it's building APIs or managing data models, we love seeing real-world applications of your skills!
Be Authentic: Let your personality shine through in your application. We value curiosity and a collaborative mindset, so don’t hesitate to share your passion for data engineering and how you approach problem-solving. We’re looking for individuals who can challenge the status quo!
Apply Through Our Website: For the best chance of success, make sure to apply directly through our website. This way, your application will be seen by the right people, and you'll be one step closer to joining our innovative team at Ki!
How to prepare for a job interview at Ki
✨Know Your Data
Before the interview, dive deep into Ki's data landscape. Familiarise yourself with their current challenges and how your skills in Python, PostgreSQL, and cloud platforms can help modernise their data estate. Being able to discuss specific examples of how you've tackled similar issues will show you're the right fit.
✨Showcase Your Collaboration Skills
Ki values teamwork, so be ready to share experiences where you've worked closely with actuaries, data scientists, or engineers. Highlight how you’ve contributed to cross-functional projects and how your collaborative mindset can help drive success in their agile environment.
✨Prepare for Technical Questions
Expect questions on API development, data modelling, and ETL/ELT processes. Brush up on your knowledge of tools like FastAPI or Flask, and be prepared to discuss how you've implemented CI/CD pipelines. Demonstrating your technical expertise will be crucial in showcasing your fit for the role.
✨Embrace the Culture
Ki is all about inclusivity and innovation. Be ready to discuss how you align with their values of knowing the customer, growing together, and being courageous. Share examples of how you've pushed boundaries in your previous roles and how you can contribute to a culture that thrives on diverse perspectives.