At a Glance
- Tasks: Lead the design and delivery of Finance Data Architecture across various financial functions.
- Company: Dynamic insurance firm at the forefront of finance data innovation.
- Benefits: Hybrid work model, competitive salary, and opportunities for professional growth.
- Other info: Join a collaborative team focused on innovative solutions in a regulated environment.
- Why this job: Shape the future of finance data with cutting-edge technology and AI integration.
- Qualifications: Expertise in finance data architecture and experience in large-scale data transformations.
The predicted salary is between 80000 - 100000 € per year.
Hybrid, London, 3 days onsite. My leading client is looking to recruit a Finance Data Architect Lead to define and lead the delivery of end-to-end Finance Data Architecture across Finance, Risk, Treasury, Tax, and Actuarial functions, leveraging CDT-provisioned platforms (e.g. Azure, Databricks).
Key Responsibilities
- Define and deliver target Finance Data Architecture, including data models, data flows, and integration patterns aligned to enterprise data strategy and CDT standards.
- Act as the primary interface with CDT teams to ensure platform readiness, scalability, and architectural alignment.
- Lead design authority across data, analytics, and reconciliation frameworks supporting statutory, regulatory, and internal reporting.
- Oversee implementation of modern data platforms, including Python-based data pipelines and lakehouse architectures on CDT environments.
- Ensure robust control frameworks, including end-to-end reconciliations across multiple reporting bases (e.g. IFRS, Solvency II, internal views).
- Embed AI capabilities into the data architecture, including GenAI-enabled reporting layers, agentic controls, and anomaly detection mechanisms.
Experience & Capabilities
- Deep expertise in insurance finance data across Finance, Risk, and Actuarial domains.
- Proven experience delivering large-scale data transformation programmes within complex, regulated environments.
- Strong track record of working with central/cloud platform teams (CDT) to deliver scalable, governed data solutions.
- Advanced understanding of AI applications in finance, particularly in reporting, controls, and data quality assurance.
If this is of interest please share your CV ASAP.
Finance Data Architecture Lead - Insurance in London employer: Experis
As a leading employer in the finance sector, our company offers a dynamic and inclusive work culture that fosters innovation and collaboration. With a strong focus on employee growth, we provide ample opportunities for professional development and advancement, particularly in cutting-edge areas like AI and data architecture. Located in London, our hybrid work model allows for flexibility while ensuring that team members can engage directly with colleagues and projects, making it an ideal environment for those seeking meaningful and rewarding careers.
StudySmarter Expert Advice🤫
We think this is how you could land Finance Data Architecture Lead - Insurance in London
✨Tip Number 1
Network like a pro! Reach out to your connections in the finance and insurance sectors. We all know that sometimes it’s not just what you know, but who you know. Attend industry events or webinars to meet potential employers and get your name out there.
✨Tip Number 2
Prepare for those interviews! Research the company and its culture, especially focusing on their data architecture and AI initiatives. We want you to be able to discuss how your experience aligns with their needs, so practice articulating your thoughts clearly.
✨Tip Number 3
Showcase your skills! Create a portfolio or case studies that highlight your previous work in finance data architecture. We believe that demonstrating your expertise can set you apart from other candidates, especially when it comes to complex projects.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets noticed. We’re always on the lookout for talented individuals like you, so don’t hesitate to submit your CV and let us help you land that dream job!
We think you need these skills to ace Finance Data Architecture Lead - Insurance in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV speaks directly to the role of Finance Data Architecture Lead. Highlight your experience in finance data, especially in insurance, and showcase any relevant projects that align with the job description.
Showcase Your Skills:Don’t just list your skills; demonstrate them! Use specific examples from your past work that illustrate your expertise in data architecture, AI applications, and working with cloud platforms like Azure and Databricks.
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Explain why you’re passionate about this role and how your background makes you the perfect fit. Be sure to mention your understanding of regulatory environments and large-scale data transformations.
Apply Through Our Website:We encourage you to apply through our website for a smoother application process. It helps us keep track of your application and ensures you don’t miss out on any important updates!
How to prepare for a job interview at Experis
✨Know Your Data Architecture Inside Out
Make sure you’re well-versed in the specifics of Finance Data Architecture, especially as it relates to insurance. Brush up on data models, flows, and integration patterns that align with enterprise data strategies. Being able to discuss these confidently will show your expertise.
✨Familiarise Yourself with CDT Platforms
Since the role involves working with platforms like Azure and Databricks, take some time to understand their functionalities and how they can be leveraged for scalable data solutions. This knowledge will help you engage effectively with CDT teams during the interview.
✨Highlight Your Experience with AI in Finance
Given the emphasis on embedding AI capabilities, be prepared to discuss your experience with AI applications in finance. Share specific examples of how you've implemented GenAI-enabled reporting layers or anomaly detection mechanisms in past projects.
✨Prepare for Scenario-Based Questions
Expect scenario-based questions that assess your problem-solving skills in complex, regulated environments. Think about past challenges you've faced in data transformation programmes and how you overcame them. This will demonstrate your ability to lead and innovate in the role.
