At a Glance
- Tasks: Build data foundations and create workflows to empower data-driven decisions.
- Company: Innovative AI-focused company with a remote-first culture.
- Benefits: Competitive salary, flexible work hours, and opportunities for professional growth.
- Other info: Remote position with a focus on collaboration and innovation.
- Why this job: Join a cutting-edge team and make a real impact on data-driven strategies.
- Qualifications: Experience in data engineering and a passion for AI technologies.
The predicted salary is between 80000 - 100000 £ per year.
About The Role
We already collect a lot of data — now we need someone to turn it into leverage. This is not a classic pipelines-and-warehouse hire (that's table stakes). It's an AI-native take on the data role: build the foundations, then the agents and internal workflows on top that make the whole organization faster and more data-driven. This is an AI-native, senior role for someone who builds. You'll work across the data substrate and the agentic layer on top of it, and you'll be measured by how much faster and smarter you make the rest of the team.
Responsibilities
- Build the data foundation — pipelines, warehouse, the substrate. Necessary, but not the point.
- Build agents and internal workflows on top of that foundation — the actual leverage.
- Enabling the org (product and beyond) to make faster, data-driven decisions.
Compensation
Compensation Range: €135K - €190K
Data Engineer (EU/UK Based - Remote) in London employer: duvo.ai
As a forward-thinking employer, we offer a dynamic work culture that prioritises innovation and collaboration, making it an ideal environment for Data Engineers looking to make a significant impact. Our remote setup allows for flexibility while providing ample opportunities for professional growth and development in the rapidly evolving field of AI and data management. Join us to be part of a team that values your contributions and empowers you to drive meaningful change across the organisation.
StudySmarter Expert Advice🤫
We think this is how you could land Data Engineer (EU/UK Based - Remote) 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 duvo.ai!
✨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 Data Engineer (EU/UK Based - Remote) at duvo.ai.
✨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 duvo.ai.
✨Apply Directly through Our Website
When you find a suitable opening like Data Engineer (EU/UK Based - Remote) at duvo.ai, 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 Data Engineer (EU/UK Based - Remote) 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 duvo.ai, 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 duvo.ai. 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 duvo.ai
✨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 duvo.ai!
✨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.
