Analytics Engineer (Hybrid) — AI-Powered Data & Fabric

Analytics Engineer (Hybrid) — AI-Powered Data & Fabric

Full-Time 51750 - 63250 £ / year (est.) Home office (partial)
Vivo Talent

At a Glance

  • Tasks: Advance our data ecosystem by delivering scalable analytics solutions using Microsoft Fabric.
  • Company: Vivo Talent, a forward-thinking company focused on AI-powered data solutions.
  • Benefits: Hybrid work model, competitive salary, and opportunities for professional growth.
  • Other info: Exciting role with potential for career advancement in the tech industry.
  • Why this job: Join us to make a real impact with data and AI in a dynamic environment.
  • Qualifications: Experience in analytics and a passion for data-driven decision making.

The predicted salary is between 51750 - 63250 £ per year.

Vivo Talent is seeking an Analytics Engineer to advance the company's data ecosystem in a hybrid role based in Kingston-Upon-Thames.

You’ll focus on analytics within the Microsoft Fabric platform, delivering scalable data solutions that empower stakeholders with accessible and actionable insights.

The role sits at the intersection of data, analytics and business value, with AI-enabled development embedded across teams to drive productivity and impact.

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Analytics Engineer (Hybrid) — AI-Powered Data & Fabric 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.

Vivo Talent

Contact Details:

Vivo Talent Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Analytics Engineer (Hybrid) — AI-Powered Data & Fabric

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 (Hybrid) — AI-Powered Data & Fabric 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

When you find a suitable opening like Analytics Engineer (Hybrid) — AI-Powered Data & Fabric at Vivo Talent, 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 Analytics Engineer (Hybrid) — AI-Powered Data & Fabric

Analytics
Microsoft Fabric
Data Solutions
AI-Enabled Development
Stakeholder Engagement
Data Ecosystem Management
Scalability

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.