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 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 - HFG 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 empowering our employees to achieve meaningful and rewarding careers.
StudySmarter Expert Advice🤫
We think this is how you could land Finance Data Engineering & Analytics Lead - HFG 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; you never know who might have a lead on your dream job!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your Python and PySpark projects. Highlight any data pipelines or analytics dashboards you've built, especially if they relate to finance or risk reporting.
✨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, as this will set you apart from the competition.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities that might just be the perfect fit for you. Plus, it’s a great way to get noticed by our hiring team directly!
We think you need these skills to ace Finance Data Engineering & Analytics Lead - HFG in London
Some tips for your application 🫡
Show Off Your Python Skills:Make sure to highlight your strong Python capabilities in your application. We want to see how you've used Python or PySpark in past projects, especially in building data pipelines or models.
Cloud Experience is Key:If you've worked with Cloud Data Platforms, let us know! Share specific examples of how you've leveraged these platforms in your previous roles, as this is vital for the position.
Finance and Actuarial Knowledge Matters:Don’t forget to mention any experience you have in Finance or Actuarial fields. We’re looking for candidates who understand the nuances of these areas, so make it clear how your background aligns with our needs.
Be Yourself!:While we love a polished application, we also want to get to know the real you. Don’t hesitate to show your personality and how you can work both independently and as part of a team. Apply through our website and let’s connect!
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 built datasets, 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 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 company's needs.
✨Showcase Your AI Knowledge
Since applying AI in delivery is part of the role, be ready to share examples of how you've integrated AI-enabled tooling in your previous work. Discuss any relevant projects that highlight your ability to leverage AI for data validation or analytics.
