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- Tasks: Enhance automation in financial workflows and solve technical challenges remotely.
- Company: Exciting property-tech start-up in the UK with a focus on innovation.
- Benefits: Market compensation in GBP and flexible remote work options.
- Why this job: Join a dynamic team and make a real impact on financial accuracy.
- Qualifications: Experience with backend code and financial data reconciliation required.
- Other info: Autonomy in your role with opportunities for personal growth.
The predicted salary is between 36000 - 60000 £ per year.
A property-tech start-up in the UK seeks a Senior System/Data Analyst to enhance automation in financial workflows involving payments for a diverse property portfolio. The ideal candidate will have autonomy in solving technical challenges and a perfectionist attitude towards financial accuracy. This remote role offers market compensation in GBP and requires comfortable engagement with backend code and financial data reconciliation.
Remote Senior Payments Data Analyst - Automate Flows employer: Dwelly
Contact Detail:
Dwelly Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Remote Senior Payments Data Analyst - Automate Flows
✨Tip Number 1
Network like a pro! Reach out to folks in the property-tech space on LinkedIn or relevant forums. A friendly chat can open doors that a CV just can't.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your past projects, especially those involving financial workflows and automation. This will give us a clear picture of what you can bring to the table.
✨Tip Number 3
Prepare for the interview by brushing up on backend coding and financial data reconciliation. We love candidates who can dive deep into technical challenges and demonstrate their problem-solving prowess.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets noticed. Plus, we’re always on the lookout for passionate individuals ready to make an impact in the property-tech world.
We think you need these skills to ace Remote Senior Payments Data Analyst - Automate Flows
Some tips for your application 🫡
Show Off Your Skills: Make sure to highlight your experience with backend code and financial data reconciliation. We want to see how you’ve tackled similar challenges in the past, so don’t hold back!
Be a Perfectionist: Since we’re all about financial accuracy, let us know how you ensure precision in your work. Share examples of how your attention to detail has made a difference in your previous roles.
Tailor Your Application: Don’t just send a generic CV! Customise your application to reflect the specific requirements of the Senior Payments Data Analyst role. We love seeing candidates who take the time to connect their experience with our needs.
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’re considered for this exciting opportunity!
How to prepare for a job interview at Dwelly
✨Know Your Numbers
As a Senior Payments Data Analyst, you'll be dealing with financial data all the time. Brush up on your financial metrics and be ready to discuss how you've used data to drive decisions in previous roles. Show them you can turn numbers into insights!
✨Showcase Your Automation Skills
Since the role focuses on enhancing automation in financial workflows, prepare examples of how you've automated processes in the past. Be specific about the tools and technologies you used, and how they improved efficiency or accuracy.
✨Get Comfortable with Backend Code
This position requires engagement with backend code, so make sure you're familiar with the relevant programming languages and frameworks. If you’ve worked on any projects involving backend systems, be ready to discuss your approach and the challenges you faced.
✨Demonstrate Your Perfectionist Attitude
Financial accuracy is key in this role. Prepare to talk about a time when your attention to detail made a significant difference in a project. Highlight how you ensure quality in your work and how you handle discrepancies in data.
