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- Tasks: Manage customer data analytics and design engaging Tableau dashboards.
- Company: Dynamic fintech firm in Northern Ireland with a collaborative culture.
- Benefits: Competitive salary, professional development, and a hybrid work model.
- Why this job: Join a forward-thinking team and present insights that drive business decisions.
- Qualifications: 5+ years in data analysis, strong SQL and Tableau skills required.
- Other info: Exciting opportunities for career growth in a fast-paced environment.
The predicted salary is between 42000 - 60000 £ per year.
A financial technology firm in Northern Ireland is looking for a Senior Data Analyst to join their team. This role involves managing customer data analytics, designing Tableau dashboards, and presenting insights to senior stakeholders.
The ideal candidate will have over 5 years of experience in data analysis within a SaaS or fintech environment, and strong skills in SQL and Tableau.
The company offers a collaborative work culture, competitive salary, and professional development opportunities.
Senior Data Analyst — Customer Insights & Dashboards (Hybrid) in Belfast employer: TeamFeePay
Contact Detail:
TeamFeePay Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Analyst — Customer Insights & Dashboards (Hybrid) in Belfast
✨Tip Number 1
Network like a pro! Reach out to folks in the fintech space, especially those who work with data analytics. A friendly chat can lead to insider info about job openings or even a referral.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your best Tableau dashboards and SQL projects. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on common data analysis scenarios. Be ready to discuss how you've used data to drive insights and decisions in previous roles. We want to see your thought process!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing candidates who are proactive about their job search.
We think you need these skills to ace Senior Data Analyst — Customer Insights & Dashboards (Hybrid) in Belfast
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience in data analysis, especially within SaaS or fintech. We want to see how your skills in SQL and Tableau shine through, so don’t hold back!
Craft a Compelling Cover Letter: Your cover letter is your chance to tell us why you’re the perfect fit for this role. Share specific examples of your past work with customer data analytics and how you've presented insights to stakeholders.
Showcase Your Dashboard Skills: Since designing Tableau dashboards is key for this role, consider including a link to your portfolio or examples of dashboards you've created. We love seeing your work in action!
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you don’t miss out on any important updates from our team.
How to prepare for a job interview at TeamFeePay
✨Know Your Data Inside Out
Before the interview, brush up on your data analysis skills, especially in SQL and Tableau. Be prepared to discuss specific projects where you've used these tools to derive insights, as this will show your practical experience and expertise.
✨Showcase Your Dashboard Design Skills
Bring examples of dashboards you've created in the past, particularly those that highlight customer insights. This not only demonstrates your technical ability but also your understanding of how to present data effectively to stakeholders.
✨Understand the Company’s Culture
Research the financial technology firm and its collaborative work culture. Be ready to discuss how you can contribute to this environment and why you’re excited about working in a team-oriented setting.
✨Prepare for Stakeholder Engagement
Since the role involves presenting insights to senior stakeholders, practice explaining complex data findings in simple terms. Think of examples where you've successfully communicated data-driven insights to non-technical audiences.
