At a Glance
- Tasks: Design and develop scalable data pipelines and AI/ML workflows in a fast-paced InsurTech environment.
- Company: Join a dynamic InsurTech company shaping the future of data strategy.
- Benefits: Competitive salary, full-time role, and opportunities for mentorship and growth.
- Other info: Collaborative culture with a focus on learning and technical excellence.
- Why this job: Make a real impact on data infrastructure while working with cutting-edge technologies.
- Qualifications: 5+ years in data engineering with strong skills in AWS, SQL, and Python.
The predicted salary is between 36000 - 60000 £ per year.
This is a senior-level opportunity for an experienced Data Engineer who is not only technically hands-on but also eager to shape the core data strategy of a fast-moving InsurTech company. You’ll play a pivotal role in designing and developing robust, scalable data pipelines, AI/ML workflows, and APIs that feed data into every part of the business—from underwriter tools to financial systems.
You’ll work in a modern, fully cloud-based stack (AWS, Snowflake, Python, SQL), with strong opportunities to influence architecture, automation, and data product direction across the company.
What you’ll be doing:
- Design, build, and maintain robust, cloud-native data infrastructure and pipelines
- Develop and manage metadata-driven data ingestion and transformation processes
- Support AI and ML infrastructure in partnership with Data Science teams
- Build APIs and data services to enable self-serve analytics and platform integrations
- Optimise data warehouse performance and reliability (Snowflake)
- Monitor data quality, pipeline health, and system observability
- Partner with cross-functional teams to understand evolving data needs
- Take ownership of key components and advocate for engineering best practices
- Mentor junior engineers and contribute to a culture of learning and technical excellence
Key Skills:
- 5+ years of experience in data engineering, ideally in a fast-paced product or platform environment
- Strong experience with AWS cloud services and infrastructure as code
- Proficiency in SQL, Python, and Snowflake
- Experience building data pipelines (batch & streaming), APIs, and ML/AI infrastructure
- Familiarity with DataOps practices, CI/CD pipelines, and modern orchestration tools
- Strong understanding of data quality, schema evolution, and monitoring in production environments
- A pragmatic mindset: you value speed and scalability but know where to invest for the long term
Please apply directly or get in touch at d.jeffery@annapurnarecruitment.com if this Data Engineering opportunity sounds like it could be the next step in your career!
Senior Data Engineer in London employer: Annapurna
Annapurna is an exceptional employer, offering a dynamic work culture that prioritises professional growth and development. As a Learning & Leadership Partner in London, you will have the unique opportunity to influence the leadership landscape within a high-growth fintech environment, while enjoying a supportive atmosphere that fosters collaboration and innovation.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Engineer in London
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Annapurna!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Senior Data Engineer at Annapurna.
✨Leverage Professional Networks
Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Annapurna.
✨Apply Directly through Our Website
When you find a suitable opening like Senior Data Engineer at Annapurna, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace Senior Data Engineer in London
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Annapurna, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Annapurna. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Annapurna
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Annapurna!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
