At a Glance
- Tasks: Design and deliver data models for banking, ensuring compliance and operational efficiency.
- Company: Leading consultancy in strategic data transformation within the banking sector.
- Benefits: Hybrid work model, competitive pay, and potential for contract extension.
- Other info: Collaborate with diverse teams and enhance your skills in a high-impact programme.
- Why this job: Make a real impact on data transformation in a dynamic banking environment.
- Qualifications: Extensive experience in data modelling, especially with Data Vault 2.0 and Snowflake.
The predicted salary is between 60000 - 80000 € per year.
Do you have the following skills, experience and drive to succeed in this role? Find out below.
Location: Glasgow (Hybrid - 2 days onsite per week)
Start Date: Immediate
Duration: Initial 6 months (extension likely)
Sector: Investment Banking
Engagement Context
Our client, a leading consultancy delivering strategic data transformation across the banking sector, is seeking a Senior Data Modeller to support a high-impact programme focused on post-bind insurance data. The successful candidate will play a critical role in designing scalable, compliant data models that underpin operational reporting, financial reconciliation, and regulatory alignment across multiple specialty lines.
Key Responsibilities
- Lead the design and delivery of conceptual, logical, and physical data models across post-bind domains.
- Collaborate with data architects, business analysts, and actuarial teams to translate complex business requirements into structured data assets.
- Apply Data Vault 2.0 methodology to support auditability, scalability, and lineage tracking.
- Model data for ingestion into Snowflake, ensuring compatibility with cloud-native architecture and downstream analytics.
- Ensure models support reconciliation of premium and claims, aged debt tracking, reserve movements, and regulatory reporting.
- Document metadata, data dictionaries, and lineage to support governance and compliance.
- Engage with stakeholders across finance, operations, and claims to validate model assumptions and ensure business alignment.
Required Experience & Skills
- Extensive experience as a Data Modeller within the FS Market, with demonstrable expertise in data.
- Proficiency in Data Vault 2.0 and dimensional modelling techniques.
- Hands-on experience with Snowflake and cloud-based data platforms.
- Ability to model across multiple specialty lines (e.g., marine, aviation, cyber).
- Strong stakeholder engagement and documentation skills.
- Clear documentation and stakeholder alignment across finance, operations, and actuarial domains.
- Seamless integration of models into Snowflake and downstream analytics pipelines.
- Contribution to a broader data transformation programme with measurable impact on operational efficiency and regulatory compliance.
Data Modeler (Banking) employer: LMA Recruitment
Join a leading consultancy in Glasgow that champions innovation and excellence in the banking sector. As a Senior Data Modeller, you will thrive in a collaborative work culture that values your expertise and offers opportunities for professional growth through impactful projects. With a hybrid working model and a focus on strategic data transformation, this role not only enhances your skills but also contributes to meaningful advancements in financial services.
StudySmarter Expert Advice🤫
We think this is how you could land Data Modeler (Banking)
✨Tip Number 1
Network like a pro! Reach out to your connections in the banking sector and let them know you're on the hunt for a Data Modeler role. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Get your online presence sorted! Make sure your LinkedIn profile is up-to-date and showcases your skills in data modelling, especially with Data Vault 2.0 and Snowflake. Join relevant groups and engage in discussions to get noticed by potential employers.
✨Tip Number 3
Prepare for interviews by brushing up on your technical skills and understanding of the banking sector. Be ready to discuss how you've applied your expertise in data modelling to solve real-world problems, especially in areas like regulatory compliance and operational efficiency.
✨Tip Number 4
Don't forget to apply through our website! We’ve got some fantastic opportunities waiting for you, and applying directly can sometimes give you an edge. Plus, it shows you're genuinely interested in joining our team!
We think you need these skills to ace Data Modeler (Banking)
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Data Modeler role. Highlight your experience with Data Vault 2.0 and Snowflake, and don’t forget to showcase your stakeholder engagement skills. We want to see how you can contribute to our data transformation programme!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're the perfect fit for this role in banking. Share specific examples of your past work that align with the responsibilities listed in the job description. Let us know how you can make an impact!
Showcase Your Technical Skills:Since this role requires hands-on experience with cloud-based platforms, be sure to highlight your technical skills clearly. Mention any relevant projects where you've modelled data for ingestion into Snowflake or worked with complex data structures. We love seeing your expertise in action!
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. Plus, it’s super easy – just a few clicks and you’re done!
How to prepare for a job interview at LMA Recruitment
✨Know Your Data Modelling Techniques
Brush up on your knowledge of Data Vault 2.0 and dimensional modelling techniques. Be ready to discuss how you've applied these methodologies in past projects, especially in the banking sector. This will show that you not only understand the theory but can also implement it effectively.
✨Showcase Your Stakeholder Engagement Skills
Prepare examples of how you've collaborated with various teams, such as data architects and business analysts. Highlight specific instances where your communication skills helped align stakeholders on complex data requirements. This is crucial for demonstrating your ability to work in a cross-functional environment.
✨Familiarise Yourself with Snowflake
Since the role involves working with Snowflake, make sure you understand its architecture and how to model data for ingestion. If possible, bring examples of how you've integrated models into cloud-native platforms before. This will give you an edge in showing your hands-on experience.
✨Prepare for Compliance and Governance Questions
Expect questions around data governance and compliance, especially related to financial reconciliation and regulatory reporting. Be ready to discuss how you've documented metadata and lineage in previous roles, as this is key for the position. Showing your understanding of these aspects will demonstrate your readiness for the role.
