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For Companies At a Glance
- Tasks: Design and develop data models for finance, CRM, and MDM projects.
- Company: Lab49 partners with top financial institutions, offering diverse challenges and growth opportunities.
- Benefits: Enjoy a hybrid work model with flexibility to work remotely or in the office.
- Why this job: Accelerate your career while working on impactful projects in a collaborative culture.
- Qualifications: 7+ years in data modeling, strong SQL skills, and experience in financial services required.
- Other info: Gain exposure to various technologies and business domains while contributing to innovative solutions.
The predicted salary is between 48000 - 84000 £ per year.
Lab49 is seeking a highly skilled Data Modeler with expertise in building application data models covering multiple capability areas of business that include Finance, CRM, and Master Data Management (MDM) to support large-scale Programmes.This role requires a strong understanding of financial services, corporate systems, and consulting environments. The ideal candidate will work closely with cross-functional teams, including data architects, business analysts, and engineers, to design robust, scalable, and compliant data solutions.Key Responsibilities:Develop conceptual, logical, and physical data models to support enterprise-wide MDM initiatives.Develop end-to-end data lifecycle event flows, mapped to logical model and physical systems.Document and maintain data dictionaries, metadata, and entity relationships.Translate requirements into optimal data structures.Define and enforce data governance policies and standards.Design data models for structured and unstructured data across relational and NoSQL databases.Ensure compliance, data security, and integrity within data models.Ability to implement models in cloud-based platforms/databases (AWS, Azure, Snowflake, etc.).Contribute to data migration, integration, and reconciliation strategies.Required Skills & Experience:7+ years of experience in data modeling and MDM.Hands-on expertise with data modeling tools (e.g., Erwin, Power Designer, ER/Studio).Strong proficiency in SQL, NoSQL, and cloud-based databases (Snowflake, Amazon Redshift, Big Query, etc.).Experience working in financial services, capital markets, or consulting environments.Deep understanding of data governance, metadata management, and regulatory compliance.Proficiency with ETL frameworks, APIs, and real-time data integration.Why Lab49?Lab49 is an established partner for most financial institutions on Wall Street. You will gain exposure to a variety of environments, business domains, technologies, and people. Your ability to bring drive and creativity to the role will be the key component to success at Lab49. The broad and intense exposure to a variety of challenges accelerates your career growth, and Lab49’s structure is designed to enable you to learn and grow as an engineer and consultant.Our Hybrid Work ModelAt Lab49, we embrace a hybrid work model, offering you the flexibility to work from the office or remotely. We expect our Lab49ers to average 3-4 days per week in person, and this could be at our midtown office in NYC or at a client site. We believe that both the flexibility and in-person connection to each other and our clients build a collaborative culture and the opportunity to accelerate growth and innovation. #J-18808-Ljbffr
Data Modeler, London employer: JobLeads GmbH
Contact Detail:
JobLeads GmbH Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Modeler, London
✨Tip Number 1
Familiarise yourself with the specific data modelling tools mentioned in the job description, such as Erwin and Power Designer. Having hands-on experience with these tools will not only boost your confidence but also demonstrate your readiness to hit the ground running.
✨Tip Number 2
Network with professionals in the financial services sector, especially those who work in data modelling or related fields. Engaging with them on platforms like LinkedIn can provide you with insights into the role and potentially lead to referrals.
✨Tip Number 3
Brush up on your knowledge of cloud-based databases like Snowflake and Amazon Redshift. Being able to discuss your experience or understanding of these platforms during interviews will show that you're well-prepared for the technical demands of the role.
✨Tip Number 4
Prepare to discuss your experience with data governance and compliance in detail. Given the importance of these areas in the role, being able to articulate your past experiences and how they relate to the responsibilities at Lab49 will set you apart from other candidates.
We think you need these skills to ace Data Modeler, London
Some tips for your application 🫡
Understand the Role: Before applying, make sure you fully understand the responsibilities and requirements of the Data Modeler position at Lab49. Familiarise yourself with key terms like MDM, data governance, and cloud-based databases.
Tailor Your CV: Customise your CV to highlight relevant experience in data modeling, financial services, and any specific tools mentioned in the job description, such as Erwin or SQL. Use keywords from the job listing to ensure your application stands out.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for data modeling and your understanding of the financial services sector. Mention specific projects or experiences that align with Lab49's needs and how you can contribute to their team.
Proofread Your Application: Before submitting, carefully proofread your CV and cover letter for any spelling or grammatical errors. A polished application reflects your attention to detail, which is crucial for a Data Modeler role.
How to prepare for a job interview at JobLeads GmbH
✨Showcase Your Data Modelling Expertise
Be prepared to discuss your experience with data modelling tools like Erwin or Power Designer. Highlight specific projects where you developed conceptual, logical, and physical data models, especially in financial services or consulting environments.
✨Demonstrate Understanding of Data Governance
Lab49 values compliance and data integrity. Be ready to explain your knowledge of data governance policies and how you've implemented them in past roles. Discuss any experience you have with metadata management and regulatory compliance.
✨Discuss Cloud-Based Solutions
Since the role involves implementing models in cloud platforms, make sure to talk about your hands-on experience with AWS, Azure, or Snowflake. Provide examples of how you've designed data models for both structured and unstructured data in these environments.
✨Prepare for Cross-Functional Collaboration Questions
As the role requires working closely with cross-functional teams, think of examples that showcase your ability to collaborate with data architects, business analysts, and engineers. Highlight how you translated requirements into optimal data structures in previous projects.
