At a Glance
- Tasks: Develop and enhance analytics solutions using Microsoft Fabric and Python.
- Company: Dynamic data-driven business embracing AI and innovation.
- Benefits: Hybrid work model, competitive salary, and opportunities for professional growth.
- Other info: Join a team where AI is already transforming productivity.
- Why this job: Shape the future of data analytics in a cutting-edge environment.
- Qualifications: Strong Python skills and experience with Microsoft Fabric and data modelling.
The predicted salary is between 45000 - 55000 £ per year.
We're partnering with an ambitious and data-driven business that is investing heavily in its analytics capability and Microsoft Fabric platform. As part of this growth, we're looking for an Analytics Engineer to help shape the future of the company's data ecosystem.
This is not a traditional Data Engineering role. Instead, we're seeking someone who enjoys working at the intersection of data, analytics and business value - building scalable solutions while ensuring data is accessible, meaningful and actionable for stakeholders across the organisation.
One of the most exciting aspects of this opportunity is the organisation's commitment to AI-enabled development. AI isn't viewed as a future initiative; it's already embedded in the way teams work.
What you'll be doing:
- You’ll play a central role in developing and enhancing the Microsoft Fabric platform, delivering solutions that support key business functions across digital, commercial and operational teams.
- Key projects include:
- Building and optimising data ingestion pipelines
- Website and digital marketing analytics
- Returns and performance reporting
- Continuous enhancement of the wider analytics platform
- You’ll also help design intuitive semantic models, improve data usability for business users and ensure data structures support natural-language AI search and reporting.
What we’re looking for:
- Strong Python development experience
- Commercial experience with Microsoft Fabric, Power BI, Semantic Models and DAX expertise
- Data modelling and pipeline development skills
- Git/version control experience
- Strong stakeholder engagement and communication skills
- Experience with dashboard development and AI-assisted development tools would be a significant advantage.
If you’re excited by the idea of building modern analytics solutions in an environment where AI is a genuine productivity multiplier, you’ll fit right in.
Analytics Engineer in London employer: Vivo Talent
Vivo Talent is an exceptional employer that fosters a supportive and dynamic work culture in Birmingham, offering a hybrid work model that promotes work-life balance. Employees benefit from competitive salaries, comprehensive professional development opportunities, and the chance to work alongside a dedicated team of experts in the mortgage industry, making it an ideal place for those seeking meaningful and rewarding careers.
StudySmarter Expert Advice🤫
We think this is how you could land Analytics 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 Vivo Talent!
✨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 Analytics Engineer at Vivo Talent.
✨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 Vivo Talent.
✨Apply Directly through Our Website
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We think you need these skills to ace Analytics 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 Vivo Talent, 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 Vivo Talent. 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 Vivo Talent
✨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 Vivo Talent!
✨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.
