At a Glance
- Tasks: Lead the development of data pipelines and analytics for finance and risk reporting.
- Company: Join a top-tier Professional Services firm with a focus on innovation.
- Benefits: Competitive salary, flexible working options, and opportunities for professional growth.
- Other info: Dynamic team environment with a focus on collaboration and independence.
- Why this job: Make an impact by applying AI and enhancing data quality in finance.
- Qualifications: Strong Python skills and experience with Cloud Data Platforms required.
The predicted salary is between 60000 - 80000 € per year.
A leading Professional Services firm is looking to hire a Finance Data Engineering Analytics Lead to join their team. You will develop Python/PySpark-based data pipelines, build data models and datasets for finance, actuarial and risk reporting. You will also develop analytics, dashboards and data validation tooling. You will also support data quality monitoring and apply AI in delivery.
KEY REQUIREMENTS:
- Strong Python capabilities
- Experience with Cloud Data Platforms is vital
- Exposure to Finance/Actuarial is essential
- Understanding of AI-enabled tooling is a necessity
- London Market Insurance experience is essential
- Be able to work independently and as part of a team.
Finance Data Engineering & Analytics Lead employer: High Finance (UK) Limited T/A HFG
As a leading Professional Services firm, we pride ourselves on fostering a dynamic work culture that encourages innovation and collaboration. Our London office offers exceptional employee growth opportunities, including access to cutting-edge technology and training in AI and data analytics, ensuring you can thrive in your role as a Finance Data Engineering & Analytics Lead. With a commitment to work-life balance and a supportive team environment, we are dedicated to helping our employees achieve meaningful and rewarding careers.
Contact Detail:
High Finance (UK) Limited T/A HFG Recruiting Team
StudySmarter Expert Advice🤫
We think this is how you could land Finance Data Engineering & Analytics Lead
✨Tip Number 1
Network like a pro! Reach out to folks in the finance and data engineering space on LinkedIn. Join relevant groups and engage in discussions; you never know who might have a lead on that perfect job.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your Python and PySpark projects. If you've built any data models or dashboards, make sure to highlight them. This will give potential employers a taste of what you can do.
✨Tip Number 3
Prepare for interviews by brushing up on your knowledge of AI-enabled tooling and cloud data platforms. Be ready to discuss how you've applied these in past roles or projects. Confidence is key!
✨Tip Number 4
Don't forget to apply through our website! We’ve got loads of opportunities that match your skills. Plus, it’s a great way to ensure your application gets seen by the right people.
We think you need these skills to ace Finance Data Engineering & Analytics Lead
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your strong Python capabilities and any experience with Cloud Data Platforms. We want to see how your skills align with the role, so don’t be shy about showcasing your finance or actuarial exposure!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you’re the perfect fit for the Finance Data Engineering & Analytics Lead role. Mention your experience with AI-enabled tooling and how you can contribute to our team.
Showcase Relevant Projects:If you've worked on projects involving data pipelines or dashboards, make sure to mention them! We love seeing real-world applications of your skills, especially in the context of finance and risk reporting.
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 the role. Plus, it shows you’re keen on joining our team!
How to prepare for a job interview at High Finance (UK) Limited T/A HFG
✨Know Your Python Inside Out
Make sure you brush up on your Python and PySpark skills before the interview. Be ready to discuss specific projects where you've developed data pipelines or models, as this will show your practical experience and problem-solving abilities.
✨Familiarise Yourself with Cloud Data Platforms
Since experience with Cloud Data Platforms is vital for this role, do some research on the platforms mentioned in the job description. Be prepared to talk about how you've used these tools in past projects and how they can enhance data engineering processes.
✨Understand the Finance and Actuarial Landscape
Having a solid grasp of finance and actuarial concepts is essential. Brush up on key terms and recent trends in the London Market Insurance sector. This knowledge will help you demonstrate your relevance to the role and your ability to contribute effectively.
✨Showcase Your AI Knowledge
Since applying AI in delivery is a necessity, be ready to discuss any experience you have with AI-enabled tooling. Share examples of how you've integrated AI into your work, and be prepared to suggest innovative ways it could be applied in the role you're interviewing for.
