At a Glance
- Tasks: Design and optimise scalable data models to enhance analytics capabilities.
- Company: Fast-growing retail subscription business focused on data transformation.
- Benefits: Competitive day rate, remote/hybrid work, and potential for contract extension.
- Other info: Open to diverse applicants; supportive recruitment process.
- Why this job: Join a major data transformation programme and influence future analytics architecture.
- Qualifications: Strong experience with dbt, SQL, and modern cloud data platforms.
The predicted salary is between 58500 - 71500 £ per year.
- Analytics Engineer
- 6-Month Contract | Immediate Start | Remote/Hybrid
We're partnering with a fast-growing retail subscription business that is investing heavily in its data platform and analytics capabilities.
As part of a major transformation programme, they're looking for a Senior Analytics Engineer to help modernise their analytics environment, improve data quality, and support the rollout of new business-critical systems and reporting capabilities.
This is a highly visible role where you'll play a key part in ensuring the business has trusted, scalable data foundations that support commercial decision-making, customer insights, performance reporting, and future AI-driven initiatives.
The role is heavily focused on analytics engineering, data modelling, and semantic layer design, rather than dashboard development.
The Opportunity
- Design, build, and optimise scalable dbt models.
- Refactor and modernise existing data models to improve performance, quality, and maintainability.
- Develop robust semantic layer definitions and trusted business metrics.
- Support large-scale data and systems transformation programmes.
- Ensure data quality through testing, monitoring, and engineering best practices.
- Enable self-service analytics across the organisation.
- Contribute to analytics engineering standards, governance, and documentation.
What We're Looking For
- Strong hands-on experience with dbt.
- Advanced SQL and data modelling expertise.
- Experience working with modern cloud data platforms.
- Strong understanding of semantic layers, metrics frameworks, and analytics engineering best practices.
- Experience modernising legacy data models and supporting platform migrations.
- Ability to operate independently in a fast-paced environment.
- Strong communication and stakeholder management skills.
- Nice to Have
- Experience with modern BI and analytics platforms.
- Airflow or similar orchestration tools.
- Python.
- Experience working with customer, CRM, e Commerce, subscription, or commercial data.
- Familiarity with AI-assisted development tools and ways of working.
Why Join?
- Be part of a major data transformation programme.
- Influence the future analytics architecture of a growing business.
- Work on projects with real visibility and business impact.
- Join an established data community with strong engineering standards.
- Help shape how data is consumed across the business, including emerging AI use cases.
- Initial 6-month contract with strong extension potential.
- Contract Length: Initial 6 Months - strong chance to extend
We're particularly interested in speaking with Analytics Engineers who enjoy solving complex data modelling challenges, improving data quality, and building trusted datasets that drive better business decisions at scale.
We encourage applicants from all backgrounds, so if there is anything we can do to make our recruitment processes better for you and to allow you to show your best self, let us know.
We also understand that some people require extra time to complete assessments, require alternative application methods and can also benefit from having interview questions or a guide to the type of questions pre-interview.
We are open to any suggestions or requests that you may have and are always looking for creative ways to assess talent.
Our commitment to you is that you should always feel safe and secure when you’re working with us.
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Analytics Engineer employer: Futureheads
As a Senior Kotlin Developer at this leading tech consultancy, you will be part of a dynamic team dedicated to delivering impactful projects for the UK government. The company fosters a collaborative work culture that prioritises employee growth through continuous learning and mentorship, while offering the flexibility of remote work with minimal office presence. With competitive pay and the opportunity to contribute to significant public sector initiatives, this role is ideal for those seeking meaningful and rewarding employment.
StudySmarter Expert Advice🤫
We think this is how you could land Analytics Engineer
✨Tap into Online Data Science Communities
Join online communities focused on data science like Kaggle, LinkedIn groups, or Reddit threads. These are goldmines for temporary gigs, as you can network with professionals and potentially hear about opportunities at companies like Futureheads before they're even advertised!
✨Show Off Your Skills With Projects
Got some cool data science projects? Showcase them on platforms like GitHub or create a personal portfolio website. This visibility is crucial for landing temporary roles—let recruiters see your actual skills in action, which can set you apart from the crowd.
✨Check Out Specialist Job Boards
For temp roles, hit up job boards dedicated to tech and data science, like Stack Overflow Jobs or DataJobs. These platforms often feature openings that you won’t find on general job sites, including contracts with companies like Futureheads.
✨Leverage University Resources
If you're currently at uni or recently graduated, tap into your school's career services. They often have connections with companies looking for temporary data science interns or contract workers, and they might even host job fairs with employers like Futureheads.
We think you need these skills to ace Analytics Engineer
Some tips for your application 🫡
Highlight Your Data Projects:When applying for a temporary data science role at Futureheads, make sure to showcase any relevant projects you've worked on. Whether it's a personal project, an academic undertaking, or contributions to an open-source initiative, detailing these experiences can really set you apart and demonstrate your practical skills.
Emphasise Your Analytical Skills:In your CV and cover letter, focus on the specific analytical skills that are key to data science. Mention any experience with statistical tools, programming languages like Python or R, and data visualisation software. Don't forget to include any certifications that may bolster your expertise!
Show Your Flexibility:Since this is a temporary role, it's important to convey your adaptability and willingness to learn. In your cover letter to Futureheads, emphasise how quickly you can get up to speed with new tools or projects. Highlight any previous experiences where you've had to adjust to new environments or challenges.
Craft a Unique Data-Driven Cover Letter:Instead of the usual generic cover letter, spice it up with some data! Maybe you’ve improved a process by 20% in a past role or cleaned a dataset with over a million entries. Use these stats to your advantage to grab Futureheads’s attention and show the tangible impact of your work.
How to prepare for a job interview at Futureheads
✨Showcase Your Analytical Skills
For a data science gig, it's crucial to demonstrate your analytical abilities. Be ready to discuss previous projects and the methodologies you used. Think about how you can quantify your impact—did your analysis improve efficiency or save costs? These are the stories that will stick with interviewers at Futureheads.
✨Brush Up on Technical Skills
You might face technical questions on tools relevant to data science, like Python, R, or SQL. Prepare to solve a problem live—perhaps they'll ask you to write a simple query or code snippet. It’s cool to talk about them, but we need to show we can do it in practice, especially in a temporary role where quick results matter.
✨Highlight Your Adaptability
Since this is a temporary position, emphasise your ability to learn quickly and adapt to new tools or workflows. Share examples of how you've thrived in fast-paced environments before, and how you can hit the ground running at Futureheads.
✨Prepare a Portfolio of Your Work
Bring your portfolio to the table—showcase projects where you've leveraged data science techniques to solve problems. Whether it’s a GitHub repository or a set of case studies, having tangible examples of your work will help you stand out and show what you bring to the team at Futureheads.
