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- Tasks: Own and refine complex credit data models in a dynamic financial environment.
- Company: Global leader in data and analytics with a focus on innovation.
- Benefits: Competitive daily rate, hybrid working, and flexible hours.
- Other info: Opportunity to work independently and shape data modelling standards.
- Why this job: Make a significant impact on core credit data used across multiple products.
- Qualifications: Strong experience in enterprise data models and financial services data.
This role requires a senior data modeller to take ownership of a complex financial data domain within a global data and analytics environment focused on defining and stabilising a core credit data model used across multiple products and consumers. You’ll be expected to operate independently, make modelling decisions with incomplete information, and leave behind a clear, buildable structure for engineering teams.
This is a hands-on modelling authority position!
THE ROLE:- Own the conceptual → logical → physical data model for a core credit domain
- Define and refine key entities such as issuer, instrument, rating, event, and time/history
- Work across fragmented and under-documented data sources to establish clean, canonical definitions
- Produce source-to-target mappings, data dictionaries, and lineage artefacts
- Ensure models are aligned with downstream delivery (data products, feeds, APIs)
- Partner with product, engineering, and domain stakeholders to drive decisions and resolve ambiguity
- Set modelling standards that others can follow and build against
- Strong experience owning enterprise data models (conceptual, logical, physical)
- Proven background in financial services data (credit, risk, markets, or reference data)
- Ability to work in messy environments and reverse-engineer existing data structures
- Experience producing canonical models and governance artefacts
- Comfortable operating independently without heavy oversight
- Strong stakeholder engagement and ability to challenge where needed
- Exposure to Snowflake / modern cloud data platforms
- Experience working with data products, feeds, or APIs
- Familiarity with Data Vault / dimensional modelling approaches
- Experience in environments with multiple data consumers and distribution channels
Senior Credit Data Modeller | Hybrid, High-Impact employer: Intelix.AI
Contact Detail:
Intelix.AI Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Credit Data Modeller | Hybrid, High-Impact
✨Tip Number 1
Network like a pro! Reach out to your connections in the financial services sector and let them know you're on the lookout for opportunities. A personal recommendation can go a long way in landing that Senior Credit Data Modeller role.
✨Tip Number 2
Prepare for those interviews by brushing up on your data modelling skills. Be ready to discuss your experience with enterprise data models and how you've tackled messy environments. We want you to shine when it comes to showcasing your expertise!
✨Tip Number 3
Don’t just apply anywhere; focus on roles that excite you! Use our website to find positions that match your skills and interests. Tailor your approach to each opportunity, highlighting your experience with credit data and stakeholder engagement.
✨Tip Number 4
Follow up after interviews! A quick thank-you email can keep you top of mind for hiring managers. Share any additional thoughts or insights you have about the role, especially if they relate to the core credit data model or governance artefacts.
We think you need these skills to ace Senior Credit Data Modeller | Hybrid, High-Impact
Some tips for your application 🫡
Tailor Your CV: Make sure your CV speaks directly to the role of Senior Credit Data Modeller. Highlight your experience with enterprise data models and financial services data, as this will show us you’re a great fit for the position.
Showcase Your Skills: Don’t just list your skills; demonstrate them! Use specific examples from your past work where you’ve owned data models or worked in messy environments. This helps us see how you can tackle the challenges we face.
Be Clear and Concise: When writing your application, keep it straightforward. We appreciate clarity, so avoid jargon unless it’s relevant. Make it easy for us to understand your experience and how it aligns with our needs.
Apply Through Our Website: We encourage you to apply through our website. It’s the best way for us to receive your application and ensures you don’t miss any important updates about the process!
How to prepare for a job interview at Intelix.AI
✨Know Your Data Models Inside Out
Make sure you’re well-versed in conceptual, logical, and physical data models. Be ready to discuss your experience with enterprise data models, especially in the financial services sector. Prepare examples of how you've tackled messy data environments and produced clean, canonical models.
✨Showcase Your Stakeholder Engagement Skills
This role requires strong collaboration with various stakeholders. Think of specific instances where you’ve successfully engaged with product, engineering, or domain teams. Highlight how you’ve navigated ambiguity and driven decisions in past projects.
✨Demonstrate Your Hands-On Modelling Experience
Since this is a hands-on position, be prepared to discuss your practical experience with data modelling. Bring examples of source-to-target mappings, data dictionaries, and lineage artefacts you've created. This will show that you can not only design but also implement effective data structures.
✨Familiarise Yourself with Relevant Technologies
Brush up on your knowledge of Snowflake and modern cloud data platforms, as well as Data Vault and dimensional modelling approaches. Being able to speak confidently about these technologies will set you apart and demonstrate your readiness for the role.