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- Tasks: Build and maintain cloud-based financial datasets using Python and AI.
- Company: Join Rimes, a leader in financial data solutions with a diverse culture.
- Benefits: Enjoy health plans, gym discounts, and a supportive work environment.
- Other info: Be part of a dynamic team with opportunities for growth and innovation.
- Why this job: Make an impact by designing ETL pipelines and integrating new data sources.
- Qualifications: Strong Python skills, data processing experience, and SQL knowledge required.
The predicted salary is between 50000 - 70000 £ per year.
Rimes is seeking a Data Developer to assist in building and maintaining cloud-based financial datasets. The role requires strong Python programming and data processing skills, an understanding of AI concepts, and familiarity with SQL.
As part of the Data Team, you will design ETL pipelines and contribute to integrating new data sources.
The position offers various benefits including health plans and gym membership discounts, promoting a diverse and inclusive workplace.
Financial Data Engineer — ETL, AI & Python employer: Rimes
Contact Detail:
Rimes Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Financial Data Engineer — ETL, AI & Python
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those working at Rimes or similar companies. A friendly chat can open doors and give you insights that might just land you an interview.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your Python projects, ETL pipelines, or any AI-related work. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for the technical interview! Brush up on your SQL and data processing skills. Practising common coding challenges can help you feel more confident when it’s time to shine.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive about their job search!
We think you need these skills to ace Financial Data Engineer — ETL, AI & Python
Some tips for your application 🫡
Show Off Your Python Skills: Make sure to highlight your Python programming experience in your application. We want to see how you've used Python in past projects, especially in data processing and ETL pipelines.
Demonstrate Your Data Knowledge: Don’t forget to mention any experience you have with SQL and AI concepts. We’re looking for someone who can integrate new data sources seamlessly, so share relevant examples!
Tailor Your Application: Take a moment to customise your application for this role. We love seeing candidates who take the time to align their skills and experiences with what we’re looking for at Rimes.
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 Rimes
✨Know Your Python Inside Out
Make sure you brush up on your Python skills before the interview. Be ready to discuss your experience with Python programming, especially in relation to data processing and ETL pipelines. Practising coding challenges can help you demonstrate your proficiency.
✨Understand AI Concepts
Since the role involves AI, it’s crucial to have a solid grasp of relevant concepts. Familiarise yourself with how AI can be applied in data engineering and be prepared to discuss any projects where you've used AI techniques. This will show your potential employer that you’re not just technically skilled but also innovative.
✨SQL Skills Are Key
Brush up on your SQL knowledge, as it’s essential for this position. Be ready to answer questions about database design, querying, and optimising performance. You might even want to practice writing some SQL queries beforehand to feel confident during the interview.
✨Show Your Team Spirit
Rimes values a diverse and inclusive workplace, so be prepared to discuss how you work within a team. Share examples of past collaborations and how you’ve contributed to a positive team environment. This will highlight your ability to fit into their culture and work effectively with others.