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: Attractive salary, flexible working options, and opportunities for professional growth.
- Other info: Collaborative team environment with a focus on career advancement.
- 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 70000 - 90000 € 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 in London employer: 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.
StudySmarter Expert Advice🤫
We think this is how you could land Finance Data Engineering & Analytics Lead in London
✨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 to get your name out there.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your Python and PySpark projects. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your knowledge of cloud data platforms and AI-enabled tooling. Be ready to discuss how you've applied these in past roles or projects.
✨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 take that extra step!
We think you need these skills to ace Finance Data Engineering & Analytics Lead in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV highlights your strong Python skills and experience with Cloud Data Platforms. We want to see how your background aligns with the Finance and Actuarial sectors, so don’t hold back on showcasing relevant projects!
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 understanding of AI-enabled tooling and how you can contribute to our team.
Showcase Your Projects:If you've worked on any data pipelines or analytics dashboards, make sure to include them in your application. We love seeing real examples of your work, especially if they relate to finance or 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 don’t miss out on any important updates from our team!
How to prepare for a job interview at 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, do some research on the platforms mentioned in the job description. Be prepared to talk about how you've used these tools in past roles 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, so you can confidently discuss how your background aligns with the firm's needs.
✨Showcase Your AI Knowledge
As AI-enabled tooling is a necessity for this role, be ready to share examples of how you've applied AI in your previous work. Discuss any relevant projects or tools you've used, and how they improved data quality or analytics outcomes.
