Lead Data Modeler

Role Overview

We are seeking a Lead Data Modeller to spearhead our comprehensive data modelling strategy and oversee the dedicated team. This leadership position demands extensive expertise in banking data domains alongside substantial delivery experience gained from prestigious consulting firms or transformation initiatives. The ideal candidate will be responsible for steering the development of enterprise-level data models, enforcing governance standards, and serving as a dependable partner to senior stakeholders, guaranteeing that data structures meet compliance requirements, facilitate risk management, enhance analytics capabilities, and drive business innovation.

Benefits & Growth Opportunities:

• Attractive salary accompanied by performance bonuses
• Comprehensive health insurance coverage
• Support for professional development and certification paths
• Engagement with pioneering AI projects
• International experience and travel prospects
• Flexible work arrangements
• Opportunities for career progression within a rapidly expanding AI organization

This position provides a rare chance to shape the future of AI deployment while collaborating with a talented cohort of professionals positioned at the cutting edge of technological advancement. The successful candidate will play a vital role in propelling our organization's success in delivering impactful AI solutions to our clients.

Key Responsibilities

• Lead the design, implementation, and upkeep of enterprise data models spanning diverse banking products, risk, treasury, and regulatory landscapes.
• Establish and uphold data modeling standards and governance frameworks designed for strictly regulated financial environments.
• Collaborate with Data Architects, Engineers, and Business Analysts to ensure data models meet organizational needs and comply with regulatory standards (Basel III, IFRS, BCBS 239, AML/KYC).
• Convert complex banking processes (credit, risk, treasury, payments, capital markets) into comprehensive and reusable data models.
• Supervise data lineage, metadata, and master data entities to guarantee adequate transparency and traceability for compliance and auditing purposes.
• Conduct impact assessments for schema changes and structural alterations, ensuring minimal disruption to core banking operations and reporting.
• Work with both consulting partners and internal teams to advance data transformation programs, facilitate system migrations, and encourage cloud integration.
• Develop data modeling strategies that support AI/ML initiatives, stress testing, scenario analysis, and customer analytics.
• Mentor and guide data modelers, instilling consulting-grade delivery standards.

Required Qualifications

• Holder of a Bachelor’s or Master’s degree in Computer Science, Data Science, Information Systems, or Finance/Engineering.
• Over 10 years of experience in data modeling with a focus on the banking sector and exposure to consulting/Big 4 project delivery.
• Demonstrated capability to construct and implement conceptual, logical, and physical data models within banking domains (risk, finance, treasury, compliance, and customer data).
• Proficient in data modeling tools (e.g., Erwin, ER/Studio, SAP PowerDesigner).
• Extensive knowledge of relational databases (Oracle, SQL Server, PostgreSQL) as well as modern platforms (Snowflake, BigQuery, Redshift).
• Experience in data governance, metadata management, and creating structures for regulatory reporting.
• Familiarity with cloud platforms (AWS, Azure, GCP) and modern data architectures (data lakes, data mesh).
• Exceptional skills in stakeholder management with a track record of presenting to C-level executives in financial institutions and regulatory bodies.

Preferred Qualifications

• Prior experience at top consulting firms (Big 4, Accenture, Capgemini, or equivalents).
• Involvement in banking transformation initiatives such as core banking replacements, regulatory reporting modernization, or data strategy projects.
• Knowledge of NoSQL/graph databases (Neo4j, MongoDB) and AI-driven modeling techniques.
• Professional qualifications (e.g., CDMP, DAMA, AWS/Azure Data Architect, CFA/FRM pertaining to finance) are highly regarded.

Tools & Technologies (Relevant Exposure):

• Data Modeling: Erwin, ER/Studio, PowerDesigner
• Banking Systems: Temenos, Finacle, Murex, Calypso
• Databases: Oracle, SQL Server, PostgreSQL, Snowflake, BigQuery, Redshift
• Governance: Collibra, Informatica, Alation
• Analytics & BI: Tableau, Power BI, SAS, Qlik
• Regulatory/Finance Context: Basel III, IFRS, BCBS 239, ICAAP/ILAAP frameworks