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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 work, flexible hours, and a supportive culture.
- Why this job: Make a real impact on data usage and collaborate with passionate professionals.
- Qualifications: Strong SQL skills and experience with Snowflake required; marketing analytics knowledge is a plus.
- Other info: Be part of a growing data team and shape the analytics stack.
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.
Spectrum IT Recruitment (South) Limited is acting as an Employment Agency in relation to this vacancy.
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 tools mentioned in the job description, especially Snowflake and Sigma. Having hands-on experience or even completing relevant online courses can give you a significant edge during interviews.
✨Tip Number 2
Network with professionals in the sustainability and data analytics sectors. Attend industry meetups or webinars to connect with potential colleagues and learn more about the company culture and expectations.
✨Tip Number 3
Prepare to discuss how you've previously translated stakeholder questions into actionable insights. Think of specific examples where your data analysis directly influenced decision-making in a business context.
✨Tip Number 4
Showcase your proactive mindset by thinking of ways to improve data accessibility and usability. Be ready to share ideas on how you would approach building self-serve analytics tools for the organisation.
We think you need these skills to ace Data Analyst
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with SQL, Snowflake, and any relevant data analytics tools like Sigma or Power BI. Emphasise your ability to communicate with both technical and non-technical teams, as this is crucial for the role.
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 examples of how you've built dashboards or reports in previous roles, and your proactive approach to problem-solving.
Showcase Relevant Projects: If you have worked on projects involving marketing analytics or cloud data stacks, be sure to include these in your application. Highlight any experience with A/B testing or statistical experimentation, as these are valuable skills for the position.
Proofread Your Application: Before submitting, carefully proofread your CV and cover letter for any errors or typos. A polished application reflects your attention to detail, which is essential for a Data Analyst role.
How to prepare for a job interview at Spectrum IT Recruitment
✨Showcase Your SQL Skills
Since strong SQL skills are crucial 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 research their mission and values. Be ready to articulate 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 a bridge between business users and the data engineering team, effective communication is key. Prepare examples of how you've successfully communicated complex data concepts to non-technical stakeholders in the past.
