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For Companies At a Glance
- Tasks: Build dashboards, develop SQL models, and translate data for decision-making.
- Company: Join a sustainability-driven scaleup making waves in the vintage market.
- Benefits: Enjoy hybrid working, flexible hours, and a supportive culture.
- Why this job: Make a real impact on data usage and work with passionate, smart colleagues.
- Qualifications: Strong SQL skills and experience with Snowflake required; marketing analytics exposure is a plus.
- Other info: Be part of a growing data team and help shape analytics tools.
The predicted salary is between 43200 - 72000 £ per year.
We’re hiring for a fast-scaling, mission-led business making waves in the sustainability space. They’ve carved out a leadership position in the vintage/antiques market and are now doubling down on data — investing in their analytics capability as they expand into new markets. This is hire #3 in their growing data team — a perfect chance to help shape their analytics stack and play a central role in driving insight across marketing, operations, and finance.
The Role: You’ll be working closely with the Chief Growth Officer and data engineering team to build scalable, self-serve analytics tools — making data accessible to the whole organisation. It’s a highly visible role, with a real impact on strategic and day-to-day decision-making.
- Building and owning dashboards and reports (Sigma preferred, Power BI/Tableau also fine)
- Developing clean, scalable SQL models in a Snowflake environment
- Translating stakeholder questions into meaningful data outputs
- Acting as a bridge between business users and the data engineering team
- Championing best practices in data governance, access, and usability
- Getting involved in emerging tools like low-code analytics and AI/agentic platforms
- Helping democratise data — enabling self-serve querying and storytelling
What You’ll Need:
- Strong SQL and experience working with Snowflake
- Familiarity with data warehouse best practices, views, stored procs, etc.
- Confidence owning dashboards and reporting for key business functions
- Ability to communicate clearly with technical and non-technical teams
- A proactive mindset — always looking for ways to simplify, automate, and improve
Nice to Have:
- Exposure to marketing analytics (CRM/automation platforms like Hubspot, Marketo, etc.)
- Experience with cloud data stacks and tools
- Some Python or R for analysis and automation
- Understanding of A/B testing or statistical experimentation
Why Join?
- Real impact — shape how the business uses data from the ground up
- Work with smart, collaborative people who genuinely care about what they do
- Healthy culture — hybrid/remote working, flexible hours, and trust-based delivery
- Plenty of scope for growth and development as the business scales
Contact Detail:
Spectrum IT Recruitment Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Analyst
✨Tip Number 1
Familiarise yourself with the specific tools mentioned in the job description, like Snowflake and Sigma. If you haven't used them before, consider taking online courses or tutorials to get a basic understanding, as this will show your commitment and readiness to hit the ground running.
✨Tip Number 2
Network with current employees or alumni from the company on platforms like LinkedIn. Engaging in conversations about their experiences can provide valuable insights into the company culture and expectations, which you can leverage during interviews.
✨Tip Number 3
Prepare to discuss how you've previously translated stakeholder questions into actionable data insights. Think of specific examples where your analytical skills made a significant impact, as this aligns perfectly with the role's requirements.
✨Tip Number 4
Stay updated on trends in sustainability and how data analytics is shaping that field. Being knowledgeable about the company's mission and how your role contributes to it can set you apart as a candidate who truly understands their goals.
We think you need these skills to ace Data Analyst
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in data analysis, particularly with SQL and Snowflake. Emphasise any projects where you've built dashboards or reports, as well as your familiarity with marketing analytics.
Craft a Compelling Cover Letter: In your cover letter, express your passion for sustainability and how your skills can contribute to the company's mission. Mention specific tools you’ve used, like Sigma or Power BI, and how you’ve successfully communicated insights to both technical and non-technical teams.
Showcase Your Projects: If possible, include links to any relevant projects or portfolios that demonstrate your ability to build scalable analytics tools or dashboards. This could be a GitHub repository or a personal website showcasing your work.
Prepare for Technical Questions: Be ready to discuss your experience with SQL and data warehousing best practices during the interview. Think of examples where you've simplified processes or improved data accessibility, as these will resonate with the role's requirements.
How to prepare for a job interview at Spectrum IT Recruitment
✨Showcase Your SQL Skills
Since strong SQL skills are a must for this role, be prepared to discuss your experience with SQL in detail. Bring examples of complex queries you've written or optimised, and be ready to explain how they contributed to business insights.
✨Understand the Company’s Mission
This company is sustainability-driven, so take some time to understand their mission and values. Be ready to discuss how your personal values align with theirs and how you can contribute to their goals in the vintage/antiques market.
✨Prepare for Technical Questions
Expect technical questions related to Snowflake and data warehousing best practices. Brush up on your knowledge of views, stored procedures, and how to build scalable models, as these will likely come up during the interview.
✨Demonstrate Communication Skills
As you'll be acting as a bridge between technical and non-technical teams, it's crucial to demonstrate your ability to communicate complex data concepts clearly. Prepare examples of how you've successfully translated stakeholder questions into actionable data outputs.
