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- Tasks: Analyse financial data and present insights to stakeholders using Excel and SQL.
- Company: Join Arrow, a forward-thinking company in Manchester focused on data-driven decisions.
- Benefits: Permanent role with competitive salary and opportunities for professional growth.
- Other info: Exciting opportunity to work with Power BI and Python in a supportive environment.
- Why this job: Make an impact by transforming data into actionable insights in a dynamic team.
- Qualifications: Degree in a relevant field and experience in data analysis required.
The predicted salary is between 30000 - 40000 £ per year.
Arrow is looking for a passionate Data Analyst to join their new data-focused team in Manchester. In this permanent, full-time role, you will handle exploratory data analysis, utilize Excel and SQL for extensive data profiling, and clearly present findings to stakeholders.
The ideal candidate will have:
- A degree in a relevant field
- Proven experience in a similar role
- Strong analytical skills
Proficiency in Excel and SQL is essential, while experience with Power BI and Python is a plus.
Data Analyst - Financial Data Insights in Manchester employer: Arrow
Contact Detail:
Arrow Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Analyst - Financial Data Insights in Manchester
✨Tip Number 1
Network like a pro! Reach out to current or former employees at Arrow on LinkedIn. A friendly chat can give us insider info and maybe even a referral!
✨Tip Number 2
Show off your skills! Prepare a mini portfolio showcasing your data analysis projects, especially those using Excel and SQL. This will help us stand out during interviews.
✨Tip Number 3
Practice makes perfect! Brush up on your SQL queries and Excel functions before the interview. We want to be ready to tackle any technical questions that come our way.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets noticed. Plus, we can keep track of our progress and follow up easily.
We think you need these skills to ace Data Analyst - Financial Data Insights in Manchester
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with Excel, SQL, and any relevant projects. We want to see how your skills match the role, so don’t be shy about showcasing your analytical prowess!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Tell us why you’re passionate about data analysis and how your background makes you a perfect fit for our team. Keep it engaging and personal!
Showcase Your Projects: If you've worked on any data analysis projects, include them in your application. We love seeing real examples of your work, especially if they involve Excel, SQL, or even Power BI and Python!
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 Arrow
✨Know Your Data Tools
Make sure you brush up on your Excel and SQL skills before the interview. Be ready to discuss specific functions or queries you've used in past projects, as this will show your hands-on experience and confidence with these tools.
✨Showcase Your Analytical Mindset
Prepare to share examples of how you've approached exploratory data analysis in previous roles. Think about a challenging dataset you worked with and how you derived insights from it. This will demonstrate your problem-solving abilities and analytical skills.
✨Communicate Clearly
Since you'll be presenting findings to stakeholders, practice explaining complex data insights in simple terms. Use storytelling techniques to make your data relatable and engaging, which will highlight your communication skills.
✨Familiarise Yourself with Power BI and Python
Even if you’re not an expert, having a basic understanding of Power BI and Python can set you apart. Mention any relevant projects or courses you've taken, as this shows your willingness to learn and adapt to new tools.