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- Tasks: Lead data modelling for wholesale loans and mentor junior team members.
- Company: Join a leading bank focused on innovation in corporate and commercial banking.
- Benefits: Enjoy competitive pay, flexible working options, and opportunities for professional growth.
- Why this job: Be at the forefront of banking technology and make a real impact in the lending space.
- Qualifications: 15+ years in data modelling with expertise in corporate banking and loan technology.
- Other info: Collaborate with diverse teams and engage with senior stakeholders globally.
The predicted salary is between 72000 - 108000 £ per year.
We are seeking an experienced data modeler who will work alongside banking SMEs to produce an across functional data domain model for CIB & Commercial banking, with a specific focus on lending/loan functions of a bank.
As a senior data modeler, you will:
- Design, develop and maintain the wholesale loans data domain model.
- Have the charisma, personality & gravitas to lead working sessions (requirements grooming) with Bankers (front, middle & back office) as well as with technology colleagues.
- Mentor junior data modellers, data architects & BAs.
- Provide thought leadership, keep abreast of the latest trends and developments with Data Architecture & related Banking technology.
- Develop technology road maps, make recommendations based on best in class technologies.
- Partner closely with multiple stakeholders across business units including IT team, Sales & Trading, Operations, Technology, Business Management, Loan Syndication and Risk and Controls to deliver results in a complex environment.
- Execute process improvement analysis, identify issues, formulate actionable opportunity recommendations, design solutions, and quantify operational benefits.
- Develop domain collateral that can be used for various leads. Define technology changes required to accommodate the Business process re-engineering for Loans implementations.
- Develop effective presentations & project update materials suitable for senior stakeholders & business partners regarding overall project progress and recommendations/decisions.
Skills Required:
- At least 15 years of experience as a data modeler/architect with experience in Corporate & Commercial banking, ideally within the lending space (stages & lifecycle).
- Expertise in data modelling and loan technology and ability to spot trends in fast changing technology.
- Experience in using data modelling software advantageous (Magicdraw, Visio).
- Combination of experience working in both corporate Bank and technology firm is desirable.
- Solution developments and support in Loan technology space is essential.
- Experience across corporate banking products and on consulting engagements desirable.
- Global client engagement experience is crucial, preferably at senior stakeholder level.
- Clear and concise written and verbal communication.
Senior Data Modeller - Wholesale Lending employer: Crisil
Contact Detail:
Crisil Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Data Modeller - Wholesale Lending
✨Tip Number 1
Network with professionals in the banking and data modelling sectors. Attend industry events, webinars, or meetups to connect with potential colleagues and stakeholders who can provide insights into the role and company culture.
✨Tip Number 2
Familiarise yourself with the latest trends in data architecture and loan technology. Follow relevant blogs, podcasts, and publications to stay updated, which will help you demonstrate your knowledge during interviews.
✨Tip Number 3
Prepare to discuss your experience in leading working sessions and mentoring junior team members. Be ready to share specific examples of how you've successfully collaborated with various stakeholders in previous roles.
✨Tip Number 4
Practice your presentation skills, as you'll need to create effective project updates for senior stakeholders. Consider using tools like PowerPoint or Prezi to enhance your delivery and make a strong impression.
We think you need these skills to ace Senior Data Modeller - Wholesale Lending
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your extensive experience as a data modeler, particularly in the corporate and commercial banking sectors. Emphasise your expertise in lending technology and any relevant software you have used, such as Magicdraw or Visio.
Craft a Compelling Cover Letter: In your cover letter, demonstrate your understanding of the role and how your background aligns with the job requirements. Mention specific projects where you've led working sessions or mentored junior team members, showcasing your leadership skills.
Showcase Relevant Experience: When detailing your work history, focus on your achievements in data modelling and any process improvements you've implemented in the lending space. Use quantifiable results to illustrate your impact on previous projects.
Prepare for Technical Questions: Anticipate technical questions related to data architecture and loan technology during the application process. Be ready to discuss trends in the industry and how you've adapted to changes in technology in your previous roles.
How to prepare for a job interview at Crisil
✨Showcase Your Experience
With at least 15 years of experience required, be prepared to discuss your previous roles in detail. Highlight specific projects where you designed or developed data models, especially in the lending space, and how they contributed to the business.
✨Demonstrate Leadership Skills
As a senior data modeller, you'll need to lead working sessions with various stakeholders. Prepare examples of how you've successfully led teams or mentored junior colleagues, showcasing your charisma and ability to communicate effectively.
✨Stay Updated on Trends
The job requires thought leadership in data architecture and banking technology. Research the latest trends and developments in these areas, and be ready to discuss how they could impact the role and the organisation.
✨Prepare for Stakeholder Engagement
Given the need to partner closely with multiple stakeholders, practice articulating your ideas clearly and concisely. Prepare to discuss how you've engaged with senior stakeholders in the past and the outcomes of those interactions.
