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- Tasks: Automate and standardise data extraction in commercial real estate.
- Company: Tech company in Greater London with a focus on innovation.
- Benefits: Flexible working environment and professional development opportunities.
- Why this job: Join a dynamic team and make an impact in the real estate sector.
- Qualifications: Degree in a relevant STEM field and Python expertise.
- Other info: Open to candidates of all experience levels.
The predicted salary is between 36000 - 60000 £ per year.
A technology company in Greater London is seeking a Software Engineer to join their team. The role involves automatic extraction, classification, and validation of financial data documents in commercial real estate. Candidates of all experience levels are encouraged to apply.
Responsibilities include:
- Developing data extraction flows
- Enhancing automation processes
Required skills include:
- A degree in a relevant STEM field
- Expertise in Python
The company offers a flexible working environment and various professional development opportunities.
Real Estate Data Engineer — Automate & Standardize Data in London employer: Proda
Contact Detail:
Proda Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Real Estate Data Engineer — Automate & Standardize Data in London
✨Tip Number 1
Network like a pro! Reach out to folks in the real estate and tech sectors on LinkedIn. A friendly chat can open doors that a CV just can't.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your Python projects, especially those related to data extraction or automation. This will give you an edge over other candidates.
✨Tip Number 3
Prepare for interviews by brushing up on common technical questions and real estate data scenarios. Practising with a friend can help you feel more confident when it’s your turn to shine.
✨Tip Number 4
Don’t forget to apply through our website! We love seeing applications directly from motivated candidates who are eager to join our team and make an impact.
We think you need these skills to ace Real Estate Data Engineer — Automate & Standardize Data in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with Python and any relevant projects you've worked on. We want to see how your skills align with the role, so don’t be shy about showcasing your achievements!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about data engineering in commercial real estate and how you can contribute to our team. Keep it concise but impactful!
Showcase Your Problem-Solving Skills: In your application, mention specific examples where you've automated processes or improved data workflows. We love seeing how you tackle challenges and enhance efficiency, so let us know what you've done!
Apply Through Our Website: We encourage you to apply directly through our website for a smoother process. It helps us keep track of applications and ensures you get all the updates about your application status!
How to prepare for a job interview at Proda
✨Know Your Tech
Make sure you brush up on your Python skills before the interview. Be ready to discuss specific projects where you've used Python for data extraction or automation. This will show that you not only understand the language but can also apply it in real-world scenarios.
✨Understand the Industry
Familiarise yourself with the commercial real estate sector and the types of financial data documents you'll be working with. Being able to speak knowledgeably about industry trends and challenges will impress your interviewers and demonstrate your genuine interest in the role.
✨Prepare for Problem-Solving Questions
Expect to tackle some technical problem-solving questions during the interview. Practice coding challenges related to data extraction and automation. This will help you think on your feet and showcase your analytical skills, which are crucial for a Data Engineer.
✨Show Your Flexibility
Since the company offers a flexible working environment, be prepared to discuss how you manage your time and adapt to changing priorities. Share examples from your past experiences where you've successfully navigated challenges while maintaining productivity.