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- Tasks: Create and optimise data models for investment banking, ensuring quality and compliance.
- Company: Join a top-tier bank known for innovation and integrity in financial services.
- Benefits: Competitive salary, professional development, and a collaborative work environment.
- Why this job: Make an impact in the financial sector with cutting-edge data solutions.
- Qualifications: Experience in data modelling and strong SQL skills required.
- Other info: Dynamic role with opportunities for growth in a global network.
The predicted salary is between 36000 - 60000 £ per year.
Our client is a tier 1 bank, a globally recognised professional services institution operating across major financial markets. The organisation provides a broad range of services including assurance, advisory, tax, risk, regulatory consulting, transaction support, and technology-enabled transformation. With a strong focus on innovation, data-driven decision-making, and regulatory excellence, the bank partners with corporations, governments, and financial institutions to manage risk, enhance performance, and navigate complex financial landscapes.
Role Requirements:
- Develop conceptual and logical data models across key investment banking domains (e.g. clients, products, trades, positions, risk, finance, market and collateral data).
- Ensure models align to agreed modelling standards, naming conventions, and reusable design patterns.
- Translate business requirements into clear, structured data models aligned to authoritative upstream sources.
- Facilitate workshops with SMEs and data teams to validate definitions and resolve data discrepancies.
- Embed modelling standards, metadata, and quality controls in line with enterprise data governance frameworks.
- Operate within a high-throughput, iterative delivery (factory) model, supporting multiple concurrent data products.
- Collaborate closely with architects, governance, engineering, onsite leadership, and offshore teams to ensure scalable and maintainable solutions.
Required Experience:
- Proven experience (typically 3-7 years) in data modelling within financial services, banking, or large enterprise environments.
- Strong expertise in conceptual, logical, and physical data modelling.
- Hands-on experience with enterprise data modelling tools (e.g. ERwin, ER/Studio, PowerDesigner, or similar).
- Advanced SQL skills and strong understanding of relational database design (e.g. Oracle, SQL Server, PostgreSQL).
- Experience designing and optimising data models for data warehouses (Kimball/Inmon methodologies), data marts, and operational data stores (ODS).
- Knowledge of dimensional modelling (star/snowflake schemas).
- Experience working with large-scale, complex, multi-source data environments.
- Understanding of data governance, metadata management, and data lineage principles.
- Familiarity with regulatory and risk data frameworks (e.g. BCBS 239) within financial services.
Data Modeller employer: Data Inc. (UK) Ltd
Contact Detail:
Data Inc. (UK) Ltd Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Modeller
✨Network Like a Pro
Get out there and connect with people in the industry! Attend meetups, webinars, or even just grab a coffee with someone who works at the bank. Building relationships can open doors that a CV just can't.
✨Show Off Your Skills
When you get the chance to chat with potential employers, don’t hold back! Share your experiences with data modelling and how you've tackled challenges in the past. Real-life examples make you memorable.
✨Tailor Your Approach
Every interaction is an opportunity! Make sure to tailor your conversations to highlight how your skills align with their needs, especially around data governance and modelling standards. It shows you're not just another candidate.
✨Apply Through Us!
Don’t forget to apply through our website! We’ve got loads of resources to help you prepare for interviews and showcase your expertise in data modelling. Let’s get you that job!
We think you need these skills to ace Data Modeller
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Data Modeller role. Highlight your experience in data modelling, especially within financial services, and showcase any relevant tools you've used. We want to see how your skills align with what we're looking for!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about data modelling and how your background fits with our client's needs. Keep it concise but impactful – we love a good story!
Showcase Your Technical Skills: Don’t forget to mention your proficiency in data modelling tools and SQL skills. Be specific about the tools you’ve used and any methodologies you’re familiar with, like Data Vault or dimensional modelling. We’re keen to see your technical prowess!
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!
How to prepare for a job interview at Data Inc. (UK) Ltd
✨Know Your Data Models
Make sure you brush up on your knowledge of conceptual and logical data models, especially in the context of investment banking. Be ready to discuss how you've developed these models in the past and how they align with business requirements.
✨Familiarise Yourself with Tools
Get comfortable with data modelling tools like ERwin or Hackolade before the interview. If you can, practice using them to create a sample model. This will show that you're not just familiar with the tools but also know how to apply them effectively.
✨Understand the Business Context
Research the bank's services and how they use data to drive decision-making. Being able to connect your technical skills to their business needs will demonstrate your understanding of the role and how you can contribute to their goals.
✨Prepare for Collaborative Scenarios
Since the role involves working closely with various teams, think of examples where you've successfully collaborated with others. Be ready to discuss how you facilitated workshops or resolved discrepancies, as this will highlight your teamwork and communication skills.